predict the corrosion rate

PREDICT®

6.0

PROGRAM FOR EVALUATION AND DETERMINATION

OF CORROSION IN STEELS

USER’S GUIDE

DOCUMENT VERSION 6.0.2

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Honeywell International, Inc.

The information contained in this document is subject to change without notice and does not

represent a commitment by Honeywell International, Inc to serve any specific purpose for any user.

The information contained in this document and the PREDICT 6.0 software is purely advisory in

nature. In no event shall Honeywell or its employees or agents have liability for damages, including

but not limited to, consequential damages arising out of or in connection with any person’s use or

inability to use the information in this document. The software described in this manual is furnished

under a license agreement and may be used or copied only in accordance with this agreement. It is

unlawful to copy the accompanying software on any medium except as specifically allowed in the

license agreement. No part of this document may be reproduced or transmitted in any form or by

any means, electronic or mechanical, including photocopying and recording, for any purpose without

the expressed written permission of Honeywell International, Inc.

Copyright © Honeywell International, Inc., 1995 - 2013. All Rights Reserved.

Windows, Excel and Word are registered trademarks of Microsoft Corporation

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Table of Contents

1. INSTALLATION ............................................................................................................................................... 5

1.1 SYSTEM REQUIREMENTS FOR INSTALLING PREDICT 6.0 ........................................................................................ 5 1.2 INSTALLATION PROCEDURE .................................................................................................................................. 5

1.2.1 Single User Installation .............................................................................................................................. 5 1.2.2 Network Installation Procedure ................................................................................................................. 6

1.3 TECHNICAL PRODUCT SUPPORT ............................................................................................................................ 6

2. PREDICT 6.0: DESCRIPTION AND UTILIZATION ................................................................................... 8

2.1 OVERVIEW – WHAT‘S NEW IN PREDICT 6.0? ........................................................................................................ 8 2.1.1 PREDICT 6.0 Features and Benefits: Detail ............................................................................................... 9 2.1.2 Benefits .......................................................................................................................................................... 10 2.1.3 Units and Conversions ................................................................................................................................... 11

2.2 WORKING WITH PREDICT 6.0 .............................................................................................................................. 13 2.2.1 Important Pointers on Using PREDICT 6.0 ................................................................................................ 19 2.2.2 Cost Analysis in PREDICT 6.0 .................................................................................................................... 20 2.2.3 Flow Modeling in PREDICT 6.0 ................................................................................................................. 22 2.2.4 Ionic Strength Calculation in PREDICT 6.0 ............................................................................................... 23 2.2.5 Corrosion Distribution Profile in PREDICT 6.0 ......................................................................................... 24 2.2.6 Multipoint Sensitivity Analysis in PREDICT 6.0 ......................................................................................... 27 2.2.7 Expert Multipoint Sensitivity Analysis in PREDICT 6.0 ............................................................................. 29 2.2.8 Multi-Point Analysis in PREDICT 6.0 ........................................................................................................ 30 2.2.9 Predicted Time to Failure Plot in PREDICT 6.0......................................................................................... 32 2.2.10 Tips and Suggestions in PREDICT 6.0 ................................................................................................... 33 2.2.11 Preferences .......................................................................................................................................... 34 2.2.12 Access to JIP Corrosion Rate Data in PREDICT 6.0 ............................................................................. 35 2.2.13 Working with the PREDICT 6.0 Wizard ................................................................................................. 38

2.3 ENVIRONMENTAL PARAMETERS IN CORROSION ASSESSMENT ............................................................................ 39 2.3.1 Hydrogen Sulfide (H2S) ............................................................................................................................ 39 2.3.2 Carbon Dioxide ........................................................................................................................................ 40 2.3.3 Chlorides .................................................................................................................................................. 40 2.3.4 Bicarbonates ............................................................................................................................................. 41 2.3.5 Temperature ............................................................................................................................................. 41 2.3.6 Acetate and Ionic Strength ....................................................................................................................... 41 2.3.7 Gas to Oil Ratio ........................................................................................................................................ 42 2.3.8 Water to Gas Ratio ................................................................................................................................... 42 2.3.9 Sulfur/Aeration ......................................................................................................................................... 43 2.3.10 Hydrogen ion Concentration (pH) ....................................................................................................... 43 2.3.11 Wall Shear Stress and Fluid Velocity .................................................................................................. 43 2.3.12 Ratio of Hydrocarbons to Water .......................................................................................................... 44 2.3.13 Corrosion Allowance ........................................................................................................................... 44 2.3.14 Service Life .......................................................................................................................................... 45 2.3.15 Type of Flow ........................................................................................................................................ 45 2.3.16 Method of Inhibition ............................................................................................................................ 45 2.3.17 Inhibition Efficiency ............................................................................................................................ 46 2.3.18 Measured pH ....................................................................................................................................... 46 2.3.19 Custom Wall Shear Stress .................................................................................................................... 47 2.3.20 Gas Flow rate – Standard / Actual ...................................................................................................... 47 2.3.21 CO2 and H2S in aqueous phase (ppm) ................................................................................................. 47

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2.3.22 Scale Protection and Water Analyses options ..................................................................................... 47 2.3.23 Dew Point ............................................................................................................................................ 48

2.4 THE PREDICT 6.0 INTERFACE MENUS AND THE TOOLBAR .................................................................................. 49 2.5 GENERAL NOTES ON CONSULTING PREDICT 6.0.................................................................................................. 54

3. TECHNICAL DESCRIPTION OF PREDICT 6.0 MODEL ........................................................................ 55

3.1 SYNOPSIS ............................................................................................................................................................ 55 3.2 INTRODUCTION ................................................................................................................................................... 55 3.3 CO2/H2S-BASED CORROSION: TECHNICAL BACKGROUND AND LITERATURE REVIEW ........................................ 56 3.4 PREDICT 6.0 MODEL DESCRIPTION ...................................................................................................................... 59

3.4.1 Role of H2S .................................................................................................................................................... 60 3.4.2 Temperature Effects ....................................................................................................................................... 62 3.4.3 Chlorides ....................................................................................................................................................... 63 3.4.4 Bicarbonates .................................................................................................................................................. 63 3.4.5 Wall Shear Stress and Liquid Velocity........................................................................................................... 64 3.4.6 Importance of Water/Gas/Oil ratios .............................................................................................................. 67 3.4.7 Oxygen/Sulfur ................................................................................................................................................ 69 3.4.8 Inhibition/Inhibition Effectiveness ................................................................................................................. 70 3.4.9 Incorporation of H2S Corrosion Data from JIP ............................................................................................ 72 3.4.10 Updated pH Prediction Model ..................................................................................................................... 73 3.4.11 Pitting Probability Model ............................................................................................................................ 76 3.4.12 Summary ...................................................................................................................................................... 77

4. FLOW MODELING IN PREDICT 6.0 .......................................................................................................... 78

4.1 OVERVIEW .......................................................................................................................................................... 78 4.2 INTRODUCTION ................................................................................................................................................... 78 4.3 VERTICAL FLOW ................................................................................................................................................. 78

4.3.1. Bubbly Flow: ....................................................................................................................................... 79 4.3.2. Slug Flow: ........................................................................................................................................... 80 4.3.3. Churn Flow: ........................................................................................................................................ 80 4.3.4. Annular Flow: ..................................................................................................................................... 81 4.3.5. Shear Stress Calculation .......................................................................................................................... 81

4.4 HORIZONTAL FLOW ............................................................................................................................................ 81 4.4.1. Flow Pattern Prediction ........................................................................................................................... 83 4.4.2. Liquid Hold-up Factor ............................................................................................................................. 84 4.4.3. Pressure Drop Calculation ....................................................................................................................... 85 4.4.4. Shear Stress Calculation .......................................................................................................................... 85

4.5 COMPRESSIBILITY FACTOR ................................................................................................................................. 86 4.6 INCLINED FLOW ............................................................................................................................................. 86

5. CORROSION DISTRIBUTION PROFILE IN PREDICT 6.0 .................................................................... 88

5.1 OVERVIEW ..................................................................................................................................................... 88 5.2 INTRODUCTION .............................................................................................................................................. 88 5.3 WATER PHASE BEHAVIOR COMPUTATIONAL BACKGROUND .......................................................................... 92

APPENDIX A: BIBLIOGRAPHY .......................................................................................................................... 94

INDEX ........................................................................................................................................................................ 97

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1. INSTALLATION

1.1 SYSTEM REQUIREMENTS FOR INSTALLING PREDICT 6.0

Requirements for using PREDICT 6.0 include:

• A Microsoft Windows compatible PC or workstation, with at least 1 GB of RAM.

• A display monitor with minimum screen resolution of 1024 X 768 or higher (1024 X 768

recommended)

• Microsoft Windows XP / Windows 7 (Windows 7 Recommended)

• A CD-ROM drive for software installation or access to internet to download installation

• Predict 6.0 utilizes the Microsoft .NET Framework, the installation package will install .NET

Framework if needed

• A hard disk with at least 200 MB of available file space

The PREDICT 6.0 system is also available in a network-compatible multi user licensed version.

Installation requirements and additional details are provided separately for multi user network

installations. Please contact Honeywell product support at [email protected] for additional details.

1.2 INSTALLATION PROCEDURE

The PREDICT 6.0 installation CD includes a setup program that installs relevant files to appropriate

directories and creates icons for end user to access program functionality.

License is enforced through a USB License key which communicates with PREDICT 6.0 installed on user

machine to identify the license. Please do not connect the USB license key prior to software installation.

Insert the Installation Disk and go through the installation steps (you will need administrative rights to

install the software correctly), and consequently connect the USB key (after the installation program

gives a message indicating installation as complete). If you have not received a USB License Key, please

refer to other licensing documentation that may have been provided separately or contact Honeywell

support for further assistance.

1.2.1 Single User Installation

You will need administrative access on the computer to install all the components correctly. Log in as

the administrator or a power user with administrative access before you begin installation.

USING CD-ROM:

Start your computer and insert the PREDICT 6.0 installation CD in the CD/DVD drive. The software is

designed for auto-start; if there is no response, please double-click on the file setup.exe and follow

instructions on individual screens to complete the installation.

mailto:[email protected]

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USING DOWNLOAD LINK:

Click on the link provided to you via email, you will be prompted to Save or Open the installation file.

Select Open (or Run from current location) and the installation will begin once the download is

completed. This may take a few minutes depending on your internet connection speed. Follow the

instructions on the individual screens to complete the installation.

PREDICT 6.0 is supplied with a USB license and security key that provides licensing protection and

upgrade capability for your copy. After completing the installation, plug in the USB Key. The new

hardware found wizard comes up in Windows XP/Vista machines; click on Next to install the driver

automatically. Please ensure that the USB key is securely attached to the USB port of the computer when

using PREDICT 6.0. The key will need to be attached to the computer any time you wish to use this

software.

Double click on the PREDICT 6.0 icon on the desktop or the Predict.exe file to begin a consultation.

Attach your USB or hardware key before and during the use of PREDICT.

1.2.2 Network Installation Procedure

Follow the same procedure as described for the single-user installation, but perform the setup on the

server and not on a stand-alone PC or a network client. Separate installation instructions are provided

along with the Network License and a special USB Network Key is required for a multi-user network

license. A single user license will not be correctly installed on a network server. If you would like to

upgrade your single user license to a multi-user network license, please contact your Honeywell sales

contact or send us an email at [email protected] for details.

1.3 TECHNICAL PRODUCT SUPPORT

Honeywell offers comprehensive technical product support programs to cater to the needs of users in

both the software utilization area as well as in corrosion and material evaluation. Technical support is

classified into two categories:

(a) If you have routine questions about using PREDICT 6.0 or have problems installing or getting the

program to execute properly, please contact support personnel at Honeywell International, Inc. for

immediate assistance:


11201 Greens Crossing Blvd.

Suite 700, Houston, TX, 77067

(281) 444-2282 (Tel.)

(281) 248-0680 (Fax)

[email protected]

(b) If you have questions about the reasoning in PREDICT 6.0 or the decision-making rules or would

like to have complete access to both the system development and technical expertise at Honeywell,

you may procure annual maintenance and enroll in the PREDICT 6.0 Technical Support Program.

The PREDICT 6.0 Technical Support Program provides several benefits, including:



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Access to all the rules and decision-making mechanisms in PREDICT 6.0

Unlimited technical support for a small, one-time fee ensuring expert attention and advise

on all related corrosion evaluation problems

Free attendance to seminars and users-group workshops conducted by Honeywell

Members of support program qualify for free upgrades as well as preferred pricing on new

versions of the program. Members also receive information about relevant changes in

technology in the PREDICT 6.0 system.

Please contact Honeywell at [email protected] if you wish to procure annual maintenance /

technical support. If you have already procured technical support, please contact Honeywell by phone or

email for any questions or problems.


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2. PREDICT 6.0: DESCRIPTION AND UTILIZATION

2.1 OVERVIEW – WHAT’S NEW IN PREDICT 6.0?

PREDICT 6.0 encapsulate state-of-the-art corrosion prediction technologies, and includes critical,

hitherto unavailable data on various aspects of corrosion prediction of carbon steels for production and

transmission applications. PREDICT 6.0, a by-product of years of corrosion research and modeling,

incorporates a completely re-worked and enhanced user interface to provide access to a comprehensive

knowledge base on corrosion decision-making. It is an easy-to-use tool that integrates effects of a

complex set of environmental parameters on carbon steel and low alloy steels to provide corrosion rate

quantification based on extensive JIP data and laboratory evaluation, as well as data from literature and

field experience.

Major aspects of PREDICT 6.0 enhancements include:

Full compatibility with Windows XP and Windows 7 32-bit & 64-bit operating systems.

Ability for users to incorporate results (wall shear stress and flow regime) from a third party flow

model.

New and more accurate pH prediction and ionic strength model that accounts for appropriate

ionic and phase behavior effects of most common acid gas components (H2S, CO2) as well as

relevant anionic and cationic species.

Ability for user to choose the balancing ion. User can choose balance type which suites to his

requirements.

Ability to provide two different water analyses for inlet and outlet conditions (or wellhead and

bottomhole conditions).

Improvised saturation pH calculations. New results screen helps users understand scaling in

system with details about FeCO3 and FeS scale formation.

Enhanced usage and ease of incorporating water production data. Users can now provide liquid

water flow rate in system and get detailed results on predicted dew point temperature and water

condensation at intermediate points in pipeline/tubing.

Ability to enter gas flow rate at actual conditions (at operating conditions).

Ability to model liquid only streams without data for gas partial pressures. User can enter CO2 &

H2S aqueous data in ppm and PREDICT 6.0 estimates equilibrium partial pressures from dissolved

gases.

Ability to evaluate the pitting model saturation calculations for FeCO3 scaling and saturation pH

calculations for predicting FeCO3 scaling.

Graphical view of time to failure based on corrosion rate and corrosion allowance input.

A more informative cost module with wide coverage of different cost components.

Enhanced exporting capabilities.

Improvised analyses capabilities with Multi Point Analysis and Expert Multi Point Sensitivity

Analysis tools that help users identify safe operating envelopes.

Tips and suggestions to assist users in performing tasks, understanding relationships and

evaluating parametric effects.

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A completely re-implemented and re-worked software interface, including the ability to automate

analyses for multiphase production systems and flowlines.

2.1.1 PREDICT 6.0 Features and Benefits: Detail

PREDICT 6.0 represents the significant upgrade undertaken by Honeywell for the PREDICT program series.

The upgrade involved a revision of the pH and corrosion prediction model, introduction of new JIP data

into program logic and implementation of a pitting probability module to give end users the ability to

assess potential for pitting in oil / gas production environments.

PREDICT 6.0 incorporates a completely revised corrosion prediction module with improved performance

for prediction of pH, corrosion scaling, persistence determination, high H2S concentration effects and

flow modeling analyses, and includes JIP data-based derivation of numerical correlations between wall

shear stress and corrosion rate. PREDICT 6.0 incorporate new data, analyses and field insights to give you

the most accurate pH and corrosion prediction solution ever. PREDICT 6.0 enhancements may be

partitioned into two groups:

1. Technology and model enhancements

2. User interface and automation enhancements

Technology and model enhancements include:

A completely revised and updated pH prediction module that incorporates a rigorous

thermodynamic and phase behavior model to accurately assess pH as a function of ionic

components.

User can specify wall shear stress and flow regime if they have specific data obtained from third

party flow modelers.

Wall wetting predictions have been improved for horizontal and inclined flows when operating

temperature is less than dew point.

Users can now provide separate water analyses data for downhole and wellhead (or inlet and

outlet) conditions.

Enhanced corrosion rate profile plot.

Improvised saturation pH calculations where the end user has a choice to consider scale

protection in system or disregard the scale protection effects.

Ability to accurately determine scaling effects due to formation of iron carbonate and iron sulfide

scales as a function of temperature and pH.

Ease of use for handling water production rate as liquid water makes evaluating corrosion rate

predictions and water phase calculations easier to understand.

Ability to enter gas flow rate at actual conditions.

Process data can be entered for dissolved gases in aqueous phase (in ppm) and converted to

equilibrium partial pressures.

Ability to characterize water phase behavior, accurately predict system dew point, and determine

if the conditions are conducive to condensation for both Gas dominated and Oil dominated

systems.

More accurate calculations for ionic strength including effect of balancing ions on ionic strength.

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Ability to perform corrosion analysis along the length of a pipeline or flow line (consisting of

multiple segments) and view graphically the variation of corrosion rates over length along with

inclination profile and water phase behavior.

Updated cost and economic analysis for integrating economic factors into corrosion analysis and

utilizing annualized cost and present worth analyses to compare various material, inhibition or

monitoring and replacement costs.

User interface and automation enhancements include,

A completely re-designed, Windows 7 based interface for enhanced efficacy and ease of use.

Ability to study and automate corrosion modeling across a whole pipeline consisting of hundreds

of segments.

New, enhanced reporting format, with ability to generate automatic PDF reports.

Module to convert data from field production report into parameters required for corrosion

analysis.

New unit conversion assistant that facilitates conversion of data values amongst different unit

systems.

User level preferences

Tips & suggestions are shown to users based on their expertise level.

Provision to enter water analysis data separately for inlet and outlet conditions.

Provision to enter gas flow rate at standard or actual conditions.

Provision to enter dissolved gas data to convert it to respective partial pressure data.

Ability for user to choose the balancing ion.

Exporting consultations with Cost analysis, MPS and Profile results.

Expert MPS tool to empower analysis capabilities.

New and extremely useful MPA tool for all users.

Ability to export all analysis results into MS Excel.

Enhanced, Windows 7 compatible user-friendly interface and context sensitive help system.

2.1.2 Benefits

Microsoft Windows based tool that can run on most common personal computers, work stations

and networks, and exploits benefits of .Net based software performance

A completely re-designed, easy to use graphical interface makes system utilization for complex tasks

simple. (See Figure 2.2)

A comprehensive tool to effectively characterize and predict the complex issues of CO2 and H2S

corrosion in production / transmission environments.

Extensive on-line help system to assist the user in understanding significance of different corrosion

evaluation parameters and their effects

Easily perform analysis of complete pipelines with corrosion prediction, pH prediction and flow

modeling for horizontal or inclined pipe sections.

Designed to effect significant reduction in time spent assessing corrosion

Access to extensive consulting and development support from Honeywell in using/customizing

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2.1.3 Units and Conversions

PREDICT 6.0 system allows utilization of both English and SI units. While the system performs an

automatic conversion from English to SI and vice versa, typical conversion factors are listed in the table

below for commonly utilized system parameters.

Parameter in PREDICT 6.0

Unit in SI system

(to convert from)

Conversion To

English

Multiply by

Pressure Bar psia 14.5

Temperature C F 1.8 and add 32

Velocity m/s ft/s 3.28

Length/thickness Mm in 0.039

Gas to Oil Ratio m3/m3 scf/bbl 5.61

Water to Gas Ratio m3/M.m3 bbl/Mscf 0.178

Yield Strength Mpa ksi .145

Corrosion Rate Mmpy mpy 39.37

Note: M.m3 stands for millions of cubic meter and Mscf denotes Millions of standard cubic feet.

Table 2.0: SI Units and Conversion Factors for Corresponding English Units

PREDICT 6.0 also provides a useful tool to convert units of common engineering values such as

flow rates, temperature and pressure into English and Metric units used in the industry. This tool,

Unit Conversion Assistant, is launched from the Tools menu and can be used to perform these

unit conversions. A screen shot of this tool is shown below in Figure 2.1

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Figure 2.1 – UNIT CONVERSION ASSISTANT IN PREDICT 6.0

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2.2 WORKING WITH PREDICT 6.0

You can launch PREDICT 6.0 in one of two ways:

1. By double clicking on the PREDICT 6.0 icon on the Desktop

2. By clicking on Start > Programs > Honeywell Software > Predict 6.0

Both options will take you to a program screen similar to one shown in Figure 2.2. From this interface,

you can choose to create a new consultation, launch a saved consultation file, and launch a wizard that

will guide you to create a new consultation or access relevant online resources.

FIGURE 2.2 – PREDICT 6.0 START UP SCREEN

Clicking on New Consultation will launch a new consultation with default values filled in. The screen

shot shown in Figure 2.3 depicts a new consultation when launched. The left pane shows consultations

that are currently open and title of the program shows the active consultation.

The main part of the screen contains five tabs for Process Data, Flow Data, Project Data, Predicted

Time to Failure and Tips & Suggestions.

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Process Data: Most of the data can be provided on the Process Data tab and includes data such as

operating conditions, production rates, gas and water analysis etc.

Flow Data: Additional data pertaining to flow modeling, density and viscosity for gas, oil and water

phases, custom roughness or custom GOR, WGR etc. may be specified through the Flow Data tab.

Project Data: The Project Data tab may be used to save project related data such as gas/oil field and well

name, name and contact information of the company or any additional comments and notes. This Project

Data will typically be included on system generated consultation reports.

Predicted Time to Failure: This tab provides users a visual indication of current corrosion rate and

predicted time to failure based on current rate. This plot is helpful tool to easily understand effect of

corrosion rate on thickness of steel for given corrosion allowance.

Tips & Suggestions: User can select from preferences if he wants to receive warnings and tips or just

critical errors. Depending on the selection, user will see tips and warnings related to bicarbonates,

chlorides, H2S and CO2 partial pressures, flow regimes, etc. This tab will be refreshed every time the

results are calculated.

The lower part of the interface (Figure 2.3) shows the calculated results for predicted corrosion rate, pH,

pitting probability, water phase behavior, saturation pH details, and total water in system and relevant

details. Detailed results for flow modeling such as flow regime, wall shear stress and liquid holdup are

presented on the Flow Results tab.

FIGURE 2.3 – PREDICT 6.0 DEFAULT CONSULTATION

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Based on the data specified for the different parameters, PREDICT 6.0 will instantaneously display the

following results:

System Bulk pH

Saturation pH and scaling information

Predicted corrosion rate displayed as corrosion index (in mpy or mmpy)

System Dew Point Temperature (for both gas dominated and oil dominated systems)

A Pitting Probability Indicator that indicates the likelihood of pitting corrosion

Yes/No indicator informing the user whether the predicted corrosion rate is within the specified

allowance for the particular system

Total water in the particular system

Predicted phase behavior of water in the system in the form of a pie chart indicating the mole

fraction of water in the vapor and liquid phase

The re-designed interface in PREDICT 6.0 makes consultations and generation of appropriate results an

easy task. The user may specify data for any of the parameters and watch the effect of that parameter on

the corrosion rate in the system. The system starts with a set of default values and calculates a corrosion

rate based on any changes to the displayed values on an as-you-see-it basis.

While PREDICT 6.0 uses a complex computational model for determining the corrosion rate, the ease-of-

use in applying the system to obtain meaningful answers is transparent. However, the answers

displayed produce results consistent with the data input by the user. Hence, it is critical that users

ensure that they provide accurate input data to obtain maximum benefit from the depth of reasoning and

functionality built into PREDICT 6.0.

The steps delineated below describe a typical PREDICT 6.0 Consultation:

1. Specification of Process Data: To begin a PREDICT 6.0 consultation, start with specifying the flow

configuration (Horizontal, Vertical or Inclined), production rates for gas, water and hydrocarbon

phases and the pipe or tube ID. PREDICT 6.0 is a modular and object oriented, and allows a change of

any parameter at any point. It is advisable however to start with the operating conditions and

production rates. The Gas to Oil Ratio (GOR) and the Water to Gas Ratio (WGR) are automatically

computed and displayed.

Predict 6.0 incorporates a change in how users provide water data. In earlier versions (4.0 and 5.0)

users would have to provide the total water in the system (liquid + vapor phase). This was identified

as one of areas of improvement by many of our users who had access to only the liquid phase water

flow rate. Changes have been made to Predict 6.0 where users can provide data either in liquid phase

water flow rate or provide a dew point temperature. Either of this inputs provide enough information

(along with operating conditions and composition) to Predict 6.0 to compute the total system water

which is used in performed water phase behavior calculations in profiles and sensitivity analyses. For

under-saturated gas, users can select the dew point check box and provide the dew point temperature

of the stream. For saturated gas streams, wet gas streams or mixed phase streams users can provide

the liquid water flow rate.

Users can provide gas flow rate either at standard or actual conditions.

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2. Specification of Gas Composition: The primary corrosive species in oil and gas production systems

are CO2 and H2S gases that dissolve in liquid water to produce an acidic system pH and form a

corrosive conductive fluid. Data for CO2 and H2S can be provided for either vapor phase (partial

pressures or mol% vapor phase data) or liquid phase (ppm aqueous). The aqueous data is used to

calculate an equilibrium partial pressure for CO2 and H2S. The partial pressure data is used for the

inlet conditions and the vapor phase mole% values are used to compute the partial pressures at the

outlet conditions. The results are automatically updated and refreshed when any change is made to

CO2 or H2S data.

If user wants the system to consider saturation pH effect while performing calculations then he must

check ―Scale Protection Applied‖ checkbox. Acid gas partial pressures, temperature, pressure, pH

and ionic strength affect the scaling tendency of iron carbonate and iron sulfide. The results shown

indicate either an ―FeS Scale‖, ―FeCO3 Scale‖ or. ―No Scale‖.

3. Specification of Inhibition Details: The effect of inhibition can also be evaluated by providing the

details about the inhibition type and efficiency. Effect of glycol injection can also be evaluated by

checking the glycol injection box and providing the details. In some cases, the system might provide

no protection due to inhibition because of high velocities or chloride concentrations. PREDICT 6.0

has in-built rules to assess the appropriate method of inhibition for a given set of conditions and can

also determine whether a specified method of inhibition is applicable or not to the specified

conditions.

4. Specification of Application Details: Corrosion Allowance and Service Life are used by PREDICT

6.0 to analyze if the corrosion allowance is sufficient to achieve the desired life based on the

predicted corrosion rate. They are also used to plot graph viz. ―Predicted Time to Failure‖ on main

screen.

5. Operating Conditions at inlet and outlet: Often, corrosion analyses are required to be performed

across a tubing string or a multiphase pipeline / flow line. In such situations, where there are a

number of points / segments to assess for corrosivity prediction, it can be a tedious task to analyze

each data point. To overcome this difficulty and save substantial time / cost associated with

corrosion prediction analysis, PREDICT 6.0 has a built in corrosion distribution profile generation

module.

Temperature and Pressure at inlet and outlet conditions are used to generate corrosion profiles along

the length of the pipe or tubing. Temperature has a strong effect on system pH and corrosion rates.

Corrosion rates significantly increase with increasing temperature. The inlet temperature and

pressure are used to predict the corrosion rate that is displayed on the screen. This is a single point

corrosion rate predicted based on the operating conditions and process data at inlet conditions. The

profile tool (Analysis Menu) can be used to generate a corrosion profile along the length of pipe or

tool. This profile tool performs the following tasks:

Generation of water phase and constituent concentration data at each point along the pipeline

Prediction of corrosion rate for each point

Graphical representation of corrosion distribution profile

Graphical representation of liquid water content in relation to pipe or tubing length

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The systems enhanced calculation rules for predicting the water content of natural gas and dew point

calculations enable accurate predictions for water condensation, a critical aspect for accurate

quantification of corrosion rates. A glance at the corrosion profile provides information about

problem spots in the pipe system where there is a high probability of water condensation and

potentially damaging corrosion rates.

6. Water Analysis: Water analysis in the form of ionic concentrations may be provided for accurate pH

and corrosion prediction. Data for Chlorides, Acetates, and Bicarbonates can be provided on the

main screen. PREDICT 6.0 handles ionic data for 15 different ionic species and computes the ionic

strength for accurate pH prediction.

Clicking on the ionic strength button launches a screen that can be used to provide the ionic

concentrations from the water analysis. Presence of elemental sulfur can be evaluated by checking

the box for presence of sulfur. PREDICT 6.0 have enhanced rules to assess corrosion damage due to

oxygen in water (and acidic systems). Users can provide water analyses data for both inlet and outlet

(or downhole and wellhead) conditions – a linear interpolation is performed between each species at

these two conditions to evaluate chemistry at intermediate locations.

PREDICT 6.0 also provides access to compelling test data that provides insights into oxygen-related

localized corrosion. A measured pH value can be used instead of the predicted pH value by clicking

the appropriate box. The ionic strength can also be specified instead of using the computed ionic

strength.

A screen shot of a typical well tubing case is shown in Figure 2.4 and Figure 2.8 shows the corrosion

profile along the length of the tubing.

7. Effect of Flow: The effect of flow rate, shear stress and flow regime on predicted corrosion rates can

also be evaluated using PREDICT 6.0. Flow parameters are very critical in both determining and

controlling corrosion effects. Erosion corrosion as well as the protection (or the lack thereof) from

corrosion films is very much a function of wall shear stress, dimensionless parameters correlating

inertial and viscous forces, fluid velocity and other hydrodynamic parameters. Custom data for

performing a flow analyses may be provided on the Flow Data tab. Density and viscosity data for the

water, gas and hydrocarbon may also be specified. Custom roughness options may be selected. Any

changes on the Flow Data tab are automatically updated on the main screen. For more information,

please see the section on flow modeling.

8. Multipoint Sensitivity Analysis: While performing corrosivity analysis, it is very helpful to

understand the effect of a particular parameter or a group of parameters. Using Multipoint

Sensitivity, users can study the effect of a number of parameters on the predicted corrosion rates or

computed pH. For instance, while analyzing a particular well, it makes sense to check the effect of a

change in production rates and how such a change would affect the corrosion rates. Or for instance,

in case of a flow line, one may need to see the effect of pipe diameter on the flow characteristics and

the predicted corrosion rate. Such sensitivity analyses can be easily performed using the Multipoint

Sensitivity Tool from the Analysis menu. Additional details are available in Section 2.2.6.

A screen shot of the Multipoint Sensitivity tool is shown in Figure 2.9

9. Expert Multipoint Sensitivity Analysis: Using MPS you can understand the effect of a particular

parameter on system. Using Expert Multipoint Sensitivity, users can study the effect of a number of

parameters on the predicted corrosion rates or computed pH. You can modify and provide ranges for

certain parameters like bicarbonates, chlorides, CO2 partial pressure, H2S partial pressure and

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temperature, and check the effect on corrosion rates and other results. Such sensitivity analyses can

be easily performed using the Expert MPS Tool from the Analysis menu.

Additional details are available in Section 2.2.7.

10. Multi-Point Analysis: PREDICT 6.0 supports analyses of multiple concurrent data points across

disparate consultations and generates results from input data in MS Excel instantly. This Multi-Point

Analysis (MPA) tool may be accessed by clicking on the MPA button from the Analysis menu.

Additional details are available in Section 2.2.8.

FIGURE 2.4 – PREDICT 6.0 TYPICAL CONSULTATION

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2.2.1 Important Pointers on Using PREDICT 6.0

As you go through a PREDICT 6.0 consultation, you will observe that the effect of a change in the

value of a parameter on the corrosion calculations is seen only when you leave that particular

data slot. For example, if the corrosion rate index for a specific set of input values that includes an

H2S value of 10 psia is predicted as 15 mpy, then, if you wish to determine the corrosion index for an

H2S value of 2 psia, simply change the value in the data slot and click on any other data slot or use

the TAB Key. PREDICT 6.0 will calculate a corrosion index with the current set of values each time

you leave a data slot and click on another.

The type of flow specified (horizontal or vertical) will determine the type of inhibition choices

available to you. Obviously, it is not very meaningful to talk of pigging in vertical flow conditions

like tubing. Further, you have to specify an appropriate method of inhibition before specifying an

inhibition efficiency range. If you choose no inhibition or just pigging where continuous inhibition

is required and indicate a high efficiency, the system will ignore your efficiency specification.

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2.2.2 Cost Analysis in PREDICT 6.0

PREDICT 6.0 incorporates a rigorous, present worth cost analysis for a given material through the Cost

icon that is available under the Tools menu. Clicking on the Cost icon displays a screen as shown in

Figure 2.5. The cost analysis module allows you to compare the costs of using different materials for a

given project using a large number of relevant factors that are typically used in performing cost analyses:

Initial Investment costs (delivery, design, construction) data such as poundage and supply.

Operating costs.

Maintenance Costs.

Taxes, Depreciation and salvage value.

Recurring annual costs.

FIGURE 2.5 - COST ANALYSIS IN PREDICT 6.0

PREDICT 6.0 takes into account different elements of project life costing to determine an annualized (per

year cost) using a specific material as well as the total cost over the life time of the project. The user has

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to specify all the input data in the data slots and click on the Calculate button. The program will display

the annualized cost and present worth after taxes based on the life of the project. You can add, edit or

delete a cost case by clicking on the buttons at the top. These cost cases are stored directly into a

database and can be accessed from each PREDICT 6.0 Consultation. This ensures that all cost cases are at

your fingertips while using PREDICT 6.0.

Life Cycle Cost Analysis (LCCA) is a method that can be applied to any capital investment decision in

which higher initial costs are traded for reduced future operating costs. The ultimate purpose of life cycle

costing and of these guidelines is to provide information for decision-making that more accurately

portrays the cost of a project alternative than first cost alone.

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2.2.3 Flow Modeling in PREDICT 6.0

PREDICT 6.0 facilitates flow regime analysis and flow modeling as well as determination of wall shear

stress and pressure drop using data about the flowing medium. Clicking on the Flow Data tab on the

main screen shows the Flow Modeling screen shown in Figure 2.6. This flow module allows the user to

predict and visualize the flow regime, calculate friction factor, assess pressure drop and the wall shear

stress, based on the flow regime by specifying some commonly available data such as:

Flow orientation, Horizontal, Vertical or Inclined

Pipe Diameter and Roughness

Water production rate, density and viscosity

Gas production rate, density and viscosity

Oil production rate, density and viscosity

The user has to specify all the input data and the results are automatically updated on the Flow Results

tab. The calculated wall shear stress, superficial velocities, flow regimes and other details are displayed.

Users can also view an animated visualization of the flow regime by clicking on the View button next to

the calculated flow regime. Additional data in the form of custom roughness, surface tension,

hydrocarbon persistency, and specific GOR and WGR can also be specified on this screen. Any changes

to the parameters on this screen are applied to the consultation as well. The effect of pipe ID, or

gas/oil/water flow rates or other parameters can also be seen on the Results Tab. A screen shot of the

flow module is shown below in Figure 2.6. For more details on Flow Modeling please refer to Chapter 4.

FIGURE 2.6 - FLOW MODELING IN PREDICT 6.0

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2.2.4 Ionic Strength Calculation in PREDICT 6.0

PREDICT 6.0 incorporate an updated, accurate Ionic Strength module to provide the foundation for

accurate pH and corrosion rate predictions. Any change in the concentration of bicarbonates, acetates or

chlorides on the main interface automatically updates the ionic strength computed for the solution. In

addition to these ions, PREDICT 6.0 evaluate a total of 16 different cationic and anionic species for their

effect of bulk system pH. These can be specified by clicking on the summation icon next to the Ionic

Strength field. This launches a screen as shown below in Figure 2.7 where water analysis data may be

provided.

In PREDICT 6.0, users can now see the amount of cation / anion required to electrochemically balance the

system. An option is provided for the user to select the type of balancing ion:

Dominant ion: Ion with largest amount among all of others of same group is selected as balancing

ion by system. This applies to both cations and anions.

Na/Cl: This is the default option and has been used in earlier versions of Predict. Sodium (Na+) and

Chloride (Cl-) are the default balancing cation and anion selected.

User Choice: User can specify their values for anions/cations using this option. Note that selecting

certain ions (bicarbonates, carbonates or acetates) can create artificially buffered systems that may be

unrealistic and lead to low corrosion rate predictions which can be very non-conservative. Users

must be careful in selecting the balancing ion correctly.

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Figure 2.7 – Ionic Strength Calculation in Predict 6.0

2.2.5 Corrosion Distribution Profile in PREDICT 6.0

PREDICT 6.0 provide a useful utility to perform an analysis for corrosion index calculation over the

length of a pipe or tubing in horizontal or vertical configuration. It is available from the toolbar by

clicking on the Profile icon under the Analyses menu.

This provides a tool for calculating the Corrosion Rates, not only at a single point in the piping system,

but over user specified number of points over the entire length of the pipe or production tubing. The

user specifies all the required information in the form of pressure and temperature conditions at pipe

inlet and outlet, the total pipe length and the number of equidistant points for corrosion analysis.

It must be noted that the operating conditions, gas composition and water analysis data need to be

specified on the Process Data Tab. For horizontal or inclined pipe analysis, the gas composition at the

inlet of the pipe is provided along with temperature and pressure at the inlet and the outlet. For tubing in

vertical flow, gas composition and water analysis at the wellhead is provided along with down hole and

wellhead pressure and temperature. Once this data is provided a corrosion distribution profile can be

generated and is shown below in Figure 2.8. Additional details for generating corrosion profiles are

available in Chapter 5.

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FIGURE 2.8 - CORROSION DISTRIBUTION PROFILE IN PREDICT 6.0

The units for corrosion rates and other input parameters are determined by the user‘s choice of units on

the main form, and may be changed at any time during the program. To learn more about compatibility

and conversion of units, please refer to section 2.1.3.

The resulting plot of corrosion index vs. the pipe length generated is displayed along with the phase

distribution of water over the length, as seen in Figure 2.8. Profile facilitates display of a default

corrosion rate Vs segment length and has tabs for showing pH and water fraction vs segment length. For

more details, please refer to Chapter 5 of this user‘s guide.

The inlet conditions, as specified on the main form, are used to estimate the corrosion index at one

specific point. The operating conditions provided for the outlet help in generating a temperature and

pressure profile over the pipe length. These profiles are estimated to be linear. With the actual values for

absolute pressure (hence calculated partial pressures), temperature, and velocity (inlet velocity is

considered as average velocity over the range); Corrosion Rates are calculated at various points the

number of which is determined by the user. These rates are then plotted against the points these were

calculated at.

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Also the system uses the computational methods of Bukacek and Maddox to compute the water content

of sour gas and along with Riedel‘s correlation for vapor pressure of water to compute the phase

distribution of water at any given point in the piping system.

For piping extending over very long distances, or for nonlinear geometry, or very high velocity

differences, it is recommended that users run a distribution for 2 or 3 separate lengths, by providing

corresponding input parameters on the lower part of corrosion profile screen. For more details on

generating a multi-segment corrosion profile please refer to Chapter 5 of this user‘s guide.

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2.2.6 Multipoint Sensitivity Analysis in PREDICT 6.0

PREDICT 6.0 provide an advanced utility to perform Sensitivity Analysis for corrosion rate, Dew Point

and pH calculation with respect to a variety of other parameters. It is available from the toolbar by

clicking on the MPS icon under the Analysis menu.

This option provides a tool for calculating the effect of a variety of different parameters such as H2S and

CO2 mol% or Acetates or Production rates etc. on the predicted corrosion rate and pH. Users can select

the upper and lower bound for the sensitivity analyses and select the number of calculations to be

performed within the limits.

The following screen shown in Figure 2.9 shows the effect of a change in H2S mole% on the predicted

corrosion rate. Additional effects of various parameters can be evaluated by choosing the X-axis

parameter from the dropdown. The effect of that parameter on the corrosion rate, pH, and system dew

point is shown in the form of three small plots. Clicking on any of these plots shows the enlarged plot in

the center of the screen.

Parameters that can be selected to be plotted on the X Axis are:

Gas Production Rate

Water Production Rate

Oil Production Rate

Temperature

Pressure

H2S mol%

CO2 mol%

Pipe or Tube ID

Acetates

Bicarbonates

Chlorides

Oxygen

Parameters that can be selected to be plotted on the Y Axis are:

Calculated pH

Calculated Corrosion Rate

Calculated Dew Point

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FIGURE 2.9 – MULTIPOINT SENSITIVITY ANALYSIS – SELECTION OF PARAMETERS

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2.2.7 Expert Multipoint Sensitivity Analysis in PREDICT 6.0

PREDICT 6.0 now incorporates a very helpful analysis tool called Expert Multi-Point Sensitivity Analysis

(Expert MPS). This tool helps in visualizing effects of critical parameters such as bicarbonates,

chlorides, CO2 partial pressure, H2S partial pressure and temperature on corrosion rate, dew point and

system pH.

Expert MPS is very user friendly as it automatically generates sensitivity analyses plots for most

common variations in these critical parameters and provides users a quick shot look at reasonable worst

cases.

Bicarbonates: Bicarbonates can be varied from ± 50 % from current value.

Chlorides: Chlorides can be varied from ± 20 % from current value.

H2S partial pressure: H2S partial pressure can be varied from ± 20 % from current value.

CO2 partial pressure: CO2 partial pressure can be varied from ± 20 % from current value.

Temperature: Temperature can be varied from ± 20 % from current value.

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2.2.8 Multi-Point Analysis in PREDICT 6.0

PREDICT 6.0 supports analyses of multiple concurrent data points across disparate piping systems and

generates results from input data in MS Excel instantly. This Multi-Point Analysis (MPA) tool may be

accessed by clicking on the MPA button on Analysis menu.

To perform a Multi-Point Analysis follow these steps:

1. Click on 'MPA' button under the "Analysis" tab.

2. Make sure you have all data ready in an Excel file generating using the MPA Template. The

MPA Template provides a format which PREDICT 6.0 accepts to import and process input data –

this template is included the program installation (<Program Installation Folder>/Template).

Depending on units preferred, copy the template file to your preferred location. Enter all

environmental and flow related inputs.

3. To perform analysis, hit ‗Import‘ button on the tool-bar. See the screenshot below.

4. Once the file is imported successfully, the analysis is performed and results along with the input

data are exported to an Excel file.

5. There is ―Save‖ button on the toolbar. This button converts each selected row of the grid to valid

Predict 6.0 consultation file and saves it to the path which is specified in Preferences section. On

Grid look for first column which titles ―Save Consultation‖. Select records which you want to

save as consultations. Then click on ―Save‖ button on toolbar. These records will be processed

and saved as consultations at pre-specified location. At the end of this process you will see

message as following:

6. Once imported, you can modify the values again. To see results again, click on ―Analyze‖. In this

way, MPA helps you in analyzing multiple cases at a single time.

7. The results can be seen in MS Excel and on Results tab as well. Results are available in Grid and

Chart formats.

The system performs all requisite computations and provides a dynamic update of MPA status, as MPA

is being performed. Once the analysis is completed, the MS Excel file will be displayed to the user. A

sample plot has been created in the template for carbon steel; such plots may easily be created for other

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alloys as needed. Users may also share the Excel Template with other users to request input data or

incorporate the template in their day-to-day reporting so that cases can be run directly using these data in

Excel.

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2.2.9 Predicted Time to Failure Plot in PREDICT 6.0

This plot is a visual representation of maximum allowable corrosion rate at given service life and the

predicted corrosion rate at given process conditions. Output of this plot is the Predicted Time to Failure

(in years) for given set of environmental and flow conditions.

Twall.: Total wall thickness

Tmin: Minimum wall thickness needed for safe operation

Every time when input data is changed the predicted corrosion rates are recalculated and this plot is

updated. If predicted time is less than service life then ―Predicted Time To Failure‖ line is shown in red.

If predicted time is more than service life then ―Predicted Time To Failure‖ line is shown in green.

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2.2.10 Tips and Suggestions in PREDICT 6.0

In order to be more informative and provide users with details and insight about corrosion assessment

and prediction, Predict 6.0 now provides users with tips and suggestions while working on consultations.

If the entered input is not valid to calculate correct results, PREDICT 6.0 logs proper message on this

view. User can view these tips in the form of tooltips at respective input fields also. Tips & Suggestions

area can be cleared with button ―Clear Tips and Suggestions‖ available on toolbar. These tips are non-

intrusive and can be customized based on the level of detail needed on the Preferences screen.

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2.2.11 Preferences

PREDICT 6.0 now saves and keeps tracks of user preferences through the Preferences module. This helps

customization the look and feel and provides an more user friendly experience.

User can:

Customize default path for saving consultations.

Customize default path for exporting all documents from PREDICT 6.0.

Customize options whether to export cost analysis, MPS, Profile data.

Set number of recent consultations to be shown on interface.

Set user level to customize the detail level of tips and suggestions that are shown.

Set the default view to either Chart or Grid for MPA

Customize the appearance and theme of the application

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2.2.12 Access to JIP Corrosion Rate Data in PREDICT 6.0

PREDICT 6.0 provides users on-the-fly access to critical JIP data encompassing over 18 flow loop tests

conducted over a period of three years for different materials and environments. These tests were

conducted on OCTG and Pipeline materials to assess corrosivity of CO2/H2S multiphase systems and to

understand and characterize corrosion in terms of H2S corrosion and scaling as well as CO2 and H2S

equilibriums as a function of environmental and flow parameters. The data presented through this tool

indicates significant effect of H2S/CO2 ratio, chloride content and temperature on corrosion behavior.

The data are presented as Corrosion Rate as a function of Shear Stress graphs and may be filtered based

on the range of data requested by the user.

These data may be accessed by clicking on the JIP data icon under the tools menu. From this screen

shown below in Figure 2.10, users may select an individual item and choose to view it as either an Excel

file or an html file.

FIGURE 2.10 – CORROSION RATE DATA FROM JOINT INDUSTRY PROGRAM

As shown in the above screen, users can also choose the CO2/H2S Ratio, Chloride concentration and the

Temperature from the drop down options to filter the data.

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Laboratory tests were conducted during the JIP using both Pipeline and OCTG materials. The materials

used were:

C-Mn L-80 (Q&T), C4130 (Q&T), C4130 (N), C-Mn N-80 (N) are the OCTG materials used as

laminar flow through electrodes (FTE‘s).

API 5L-X65, A106 Gr B, API 5L-X60 are the Pipeline materials used as laminar flow though

electrodes (FTE‘s).

A summary of the test conditions for all the 18 flow loops is presented in Table 2.13

Steel Identifier Heat Treatment Carbon

percent

Cr

percent

Steel Grade/Supplier

Carbon Steel 1 Hot Rolled >= 0.1 0.0 ASM A106-Gr. B

Carbon Steel 2 Normalized/TMCP <= 0.1 0.0 API 5L x60

Low alloy steel 1 Hot Rolled >= 0.1 0.5 Siderca 0.5 Cr X65

FIGURE 2.11 – PIPELINE STEELS USED FOR TESTING IN JOINT INDUSTRY PROGRAM

Steel Identifier Heat Treatment Carbon

percent

Cr

percent

Steel Grade/Supplie

r

C-Mn steel 1 Quenched & Tempered

0.2 - 0.3 0.0 C-Mn L-80

C-Mn steel 2 Normalized 0.35 - 0.45 0.0 C-Mn N-80

Low Alloy steel 1

Gr. 4130

Quenched & Tempered

0.2 - 0.3 0.5 - 1.0 L-80 (4130)

Low Alloy steel 2

Gr. 4130

Normalized 0.35 - 0.45 0.5 - 1.0 Siderca SD-70

TABLE 2.12 - OCTG STEELS USED FOR TESTING IN JOINT INDUSTRY PROGRAM

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Test # H2S , psia CO2, psia CO2/ H2S Cl- Content, ppm Temperature, F pH

Pipeline Material

1 0.4 20 50 2000 80 3.9

2 4 20 5 2000 80 3.9

3 0.4 20 50 150000 80 3.9

OCTG Material

4 0.4 20 50 150000 80 3.9

5 4 20 5 2000 80 3.9

6 0.534 20 50 150000 80 3.9

7 35.0 200 50 2000 250 3.8

8 5.34 200 500 2000 250 3.9

9 35.0 200 5 150000 250 3.9

10 4 200 50 150000 250 3.9

11 0.4 200 500 150000 250 3.9

12

5.45 1500 250 50000 250 3.9

Pipeline Material

13 0.4 200 500 2000 200 3.9

14 0.4 20 50 150000 200 3.9

15 4 200 50 150000 200 3.9

16 4 200 50 2000 80 3.9

17 4 20 5 150000 80 3.9

18 0.4 200 500 5000 80 3.9

TABLE 2.13 - SUMMARY OF TEST CONDITIONS FOR THE JOINT INDUSTRY PROGRAM

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2.2.13 Working with the PREDICT 6.0 Wizard

PREDICT 6.0 incorporate a consultation wizard designed to assist the end user with setting up a

consultation. The user is presented with a series of questions pertaining to corrosion assessment of

oil/gas production and transmission systems. Based on the answers selected by the user and the data

provided, the wizard automatically sets up a consultation with the correct parameters. The wizard may

be launched from the main start-up page. A screenshot of the wizard is shown below in Figure 2.14.

The wizard essentially steps through the various steps of a consultation prompting user input for

operating conditions, flow rates, composition etc. at appropriate times during the process. Based on the

options selected by the user and the data provided, the Wizard will make appropriate decisions as to the

information required to complete the consultation.

Users may use the Next and Back button to navigate between the various steps and change their

responses at any time. Additional details about these questions and how the answers affect the

consultation are provided on the lower part of the screen.

At the end of this process, clicking on the Finish button will create a new consultation file with the data

that was provided to the wizard.

FIGURE 2.14 – WORKING WITH THE PREDICT 6.0 WIZARD

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2.3 ENVIRONMENTAL PARAMETERS IN CORROSION ASSESSMENT

As the user specifies environmental data, the program calculates and displays a corrosion rate index, a

direct measure of corrosion rate in the system based on a large number of parameters listed below:

Acid gases—H2S and CO2

HCO3-

Chlorides

Temperatures

Acetate and Ionic Strength

Gas to Oil Ratio

Water to Gas Ratio/Water cut

Presence of elemental sulfur/aeration

Fluid velocity

Type of flow

Inhibition and inhibition efficiency

Dew point

PREDICT 6.0 determine the system pH based on acid gas partial pressures, buffering and temperature.

The system also includes the effect of saturation53, 54

of FeCO3 and FeS scale into the corrosion index

calculation. The pH is dynamically displayed on the screen as the user specifies environmental data.

2.3.1 Hydrogen Sulfide (H2S)

Hydrogen Sulfide (H2S), like carbon dioxide is an acid gas, which dissolves in aqueous environments to

contribute to a reduction in the system pH. The pH varies with the amount of H2S dissolved. Typically,

the pH decreases with increasing amounts of H2S in solution. Lower the pH, the more aggressive the

environment from the standpoint of corrosion. Additionally, the severity of hydrogen charging also

increases with the amount of H2S. The amount of H2S in solution increases with:

1. Increasing total system pressure with the same H2S mole% causing an increase in H2S partial

pressure.

2. Increasing partial pressure at constant total system pressure if additional souring of the gas occurs

(due to increasing mole % of H2S).

Corrosion in steels generally increases with H2S partial pressure. H2S is an acid gas and the term acid

refers to its ability to depress pH when it is dissolved in an aqueous solution. This increased aggressivity

results from the decrease in the pH of the aqueous phase as the partial pressure of H2S increases. An

added effect of H2S in CO2/brine systems is a reduction in corrosion rate of steel when compared to

corrosion rates under conditions without H2S. This reduction in corrosion rate is primarily a low

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temperature effect and dominates system corrosivity at temperatures less than 175 F (80 C) due to the

formation of a meta-stable iron sulfide film. At higher temperatures the combination of H2S and

chlorides will usually produce higher corrosion rates than just CO2/brine systems, since stable iron

carbonate films usually do not occur as readily in systems with H2S as they do in systems without H2S.

With additional data from Joint Industry Program on Prediction and Assessment of Corrosivity of

Multiphase CO2/H2S systems and updated corrosion prediction / pH models, PREDICT 6.0 can accurately

predict corrosion rates for H2S partial pressure up to 500 psia.

2.3.2 Carbon Dioxide

Carbon Dioxide (CO2), as in the case of hydrogen sulfide, is an acid gas that dissolves in aqueous

environments to produce a reduction in the system pH. Therefore the pH varies with the amount of CO2

dissolved. Typically, the pH decreases with increasing amounts of CO2 in solution. Lower the pH, the

more aggressive the environment from the standpoint of corrosion. The amount of CO2 in solution

increases with increasing mole fraction of CO2 in the gas phase and with increasing partial pressure of

CO2.

Corrosion severity generally increases with CO2 partial pressure. CO2 is an acid gas and the term acid

refers to its ability to depress pH when it is dissolved in an aqueous solution. This increased aggressivity

results from the decrease in the pH of the aqueous phase as the partial pressure of CO2 increases.

CO2 partial pressures up to 1000 psia can now be analyzed using PREDICT 6.0 with the help of the

updated pH and corrosion prediction model.

2.3.3 Chlorides

Produced water from hydrocarbon formations typically contains varying amounts of chloride salts

dissolved in solution. The chloride concentration in this water can vary considerably, from zero to few

ppms for condensed water to saturation in water having high total dissolved salts/solids (TDS). In many

cases, the water in the system will be a combination of produced and condensed water resulting in

solutions with 1000 to 100,000 ppm chloride. Chlorides are often specified in ppm NaCl. It should be

noted that ppm chlorides can be obtained as 0.63 x ppm NaCl.

Under normal circumstances, the chloride content of the aqueous phase does not directly affect the

hydrogen charging conditions in steel. However, it can have an effect on the effectiveness of chemical

corrosion inhibitors. Therefore, in many cases, more careful selection of inhibitors and inhibition

procedures must be performed where high levels of chlorides (>30,000 ppm) are present.

In naturally deaerated production environments, corrosion rate increases with increasing chloride ion

content over the range 10,000 ppm to 100,000 ppm. The magnitude of this effect increases with

increasing temperature over 150 F (60 C). This combined effect results from the fact that chloride ions in

solution can be incorporated into and penetrate surface corrosion films which can lead to destabilization

of the corrosion film and increased corrosion. This phenomenon of penetration of surface corrosion films

increases in occurrence with both chloride ion concentration and temperature.

Corrosion rates of steel in oil and gas production generally increase with increasing chloride content.

The chloride species in the aqueous phase can work to penetrate and destabilize protective surface films.

Typically, brines with low chloride content (i.e. <10,000 ppm) less aggressive than those having higher

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chloride contents provided that they are compared at the same pH. In some cases, the presence of salts

can reduce the solubility of acid gases or buffer the water therefore affecting the solution pH.

2.3.4 Bicarbonates

The bicarbonate ion is a buffering agent used in aqueous solutions to increase the pH of the solution. Its

presence is typically measured in ppm or mili-equivalents/liter (meq/l). One meq/l represents 0.061

grams of HCO3- in one liter of solution or 61 ppm. The increase in pH in turn decreases the corrosivity

of the environment. Hence, presence of HCO3-

is beneficial from the standpoint of corrosion. Typical

quantities of HCO3- in production environments range from 1 meq/l to 100 meq/l.

2.3.5 Temperature

Temperature is a critical parameter in determining the corrosivity of oil and gas production

environments. Changes in temperature affect the corrosion rate of steels in several ways which must be

taken into account for estimation of corrosion severity:

1. Increasing temperature decreases solubility of dissolved gases, which increases the pH of the

environment.

2. Increasing temperature increases the aggressivity of chloride ions in aqueous solutions by thermal

activation.

3. Different levels of temperature have different effects on environmental cracking. Between room

temperature and 250ºF, increasing temperature decreases susceptibility to Hydrogen Embrittlement

Cracking and SSC. But, above 150ºF, susceptibility to Stress Corrosion Cracking is increased.

4. Formation of a protective carbonate scale in aqueous CO2 environments at elevated temperatures.

5. Reduction in CO2 corrosion rate with addition of H2S.

In the PREDICT 6.0 program, each of these effects is handled separately through the various parameters.

However, directly incorporated into the temperature effect is No. 4 in the list above (i.e. formation of a

protective iron carbonate scale in CO2 brine systems at temperatures above 150 F (60 C). This has the

effect of decreasing the corrosion rate at temperatures above 150 F (60 C) to values lower than those

usually predicted based on aqueous CO2 corrosion. However formation of iron carbonate scale itself

requires a substantial metal loss that can cause a failure. Also, the scale formation effect is not found

when H2S is present in amounts above 0.05 psia. Here, corrosion rate will normally continue to increase

with increasing temperature.

2.3.6 Acetate and Ionic Strength

The acetate ion concentration is an important parameter in calculating the bulk pH of the solution as well

as the saturation pH calculation (for FeCO3, FeS scale formation). Presence of acetate is typically

measured in ppm or mili-equivalents/liter (meq/l). One meq/l represents 0.059 grams of CH3COO- in

one liter of solution or 59 ppm. Its presence increases the pH, which in turn decreases the corrosivity of

the environment. Hence, presence of CH3COO-

is beneficial from the standpoint of corrosion. The

presence of formate (HCOO-) ions in the environment can also be interpreted as acetate ions, since both

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the acids have similar dissociation constants. Typical quantities of CH3COO- in production

environments range from 1 ppm to 200 ppm.

The Ionic Strength of a solution is an important parameter in calculating accurate pH and saturation pH

data. The ionic strength of the solution, typically represented in Molar units, can be calculated from the

individual ion concentration using:

Where,

Z is the charge of each ion

IS is the ionic strength of the solution

M is the molar concentration of each ion and can be calculated using,

Where,

x is concentration of each ion in ppm

MW is the molecular wt/ atomic wt. of each ion

Note: Predict 6.0 incorporates acetate ion concentration in calculation of in-situ pH of the system – the

presence of acetates tends to buffer the in-situ pH higher. Some data has been published that indicates an

adverse effect on corrosion through pitting and cracking in the presence of acetate. However, there have

been reports that contradict these findings as well. Currently Predict 6.0 does not take into consideration

the effects of acetate on pitting/ cracking or corrosion due to acetic acid and the acetate input is used

only to predict the in-situ pH.

2.3.7 Gas to Oil Ratio

In oil and gas production, where the environment has a GOR < 890 m3/m

3 (5000 scf/bbl in British units),

the tendency for corrosion and environmental cracking is substantially reduced. This is caused by the

inhibiting effect of the oil film on the metal surface, which effectively reduces the corrosivity of the

environment. However, the inhibiting effect is dependent on the oil phase being persistent and acting as

a barrier between the metal and the corrosive environment. If GOR is not known, it is recommended

that a value greater than 5000 scf/bbl or 890 m3/m3 be used to evaluate conditions for gas producing

systems.

2.3.8 Water to Gas Ratio

To have corrosion in oil and gas systems, presence of aqueous water is required. In many production

applications where essentially dry hydrocarbons are being produced, the full corrosivity of the hydrogen

sulfide and/or carbon dioxide will not be present.

)ZM(5.0IS 2

MW10xM

-3

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For lower Water to Gas Ratio the corrosive severity is substantially reduced. Care should be taken to

evaluate presence of possible locations where water can separate from the hydrocarbons and form a

continuous water phase. Under such conditions, substantial corrosion can exist. If you do not know the

water to gas ratio or do not wish take its effect into the reasoning, please use a value that shows liquid

water presence for that condition. The presence of liquid water is shown by the pie-chart on the Results

tab and also presented as an output. Providing a low WGR that leads to no liquid water presence will

show no predicted corrosion rates for that condition.

2.3.9 Sulfur/Aeration

In systems containing high levels of H2S, elemental sulfur is often found to be present. Its presence can

significantly increase the corrosivity of the production environment with respect to weight loss

corrosion, localized corrosion and susceptibility to sulfide stress cracking.

Aeration in the operating environment significantly increases the corrosivity of the operating

environment. In this program, the acceleration for corrosion of steel in aerated conditions is

approximately ten times that of the rate determined for deaerated conditions. Aeration also increases the

severity of localized corrosion and SCC for susceptible corrosion resistance alloys. The mechanism of

this increased aggressivity is a result of the ease of formation of oxygen concentration cells on the metal

surface, which increases pitting and crevice corrosion. Both these phenomena, in turn, increase the

severity for SCC since pitting and crevice attack can act as locations of SCC initiation.

2.3.10 Hydrogen ion Concentration (pH)

Corrosion rates generally increase with decreasing pH of the aqueous phase. Therefore, corrosivity can

be expected to increase with increasing acid gas (H2S and CO2) partial pressure. At a particular acid gas

partial pressure, pH will tend to increase with increasing temperature. This affect can result in direct

reduction in corrosion rate with this rise in pH. In many cases however, the decrease in acid gas

solubility in the aqueous phase with increasing temperature can be compensated by increased total

pressures as the well depth increases. This can actually increase acid gas partial pressure and increase the

severity of corrosion.

2.3.11 Wall Shear Stress and Fluid Velocity

In multiphase (i.e. gas, water liquid hydrocarbon) production, the flow rate influences the corrosion rate

of steel in two ways. First, it determines the flow behavior and affects wall wetting. In general terms,

with increasing velocity this is manifested as static conditions (i.e. little or no flow), stratified flow at

intermediate conditions and turbulent flow at higher flow rates. Second, flow can also accelerate

corrosion with increasing velocity through increased mass transport and at still higher flow rates by

removal of protective corrosion films (i.e. corrosion products and inhibitor films). One measure which

can be used to define the flow conditions in multiphase flow systems is the superficial liquid velocity. At

less than about 3 ft/sec (1 meter/sec), conditions are generally considered static.

Under these conditions corrosion rates can actually increase over those observed under moderate flowing

conditions. This occurs because under static conditions, there is no natural turbulence to assist the

mixing and dispersion of protective liquid hydrocarbons or inhibitor species in the aqueous phase.

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Additionally, corrosion products and other deposits can settle out of the liquid phase to promote crevice

attack and under-deposit corrosion.

Between 3 and 10 ft/sec (1 and 3 meter/sec), stratified conditions generally still exist. However, the

increased flow promotes a sweeping away of some deposits and increasing agitation and mixing. At

about 15 ft/sec (5 meter/sec), corrosion rates in non-inhibited applications start to increase rapidly with

increasing velocity. For inhibited applications, corrosion rates of steel increase only slightly between 10

and 30 ft/sec (3 to 10 meter/sec) resulting from mixing of the hydrocarbon and aqueous phases. Above

about 30 ft/sec (10 meter/sec), corrosion rates in inhibited systems start to increase due to the removal of

protective surface films by the high velocity flow.

Vertical flow conditions commonly follow similar relationships as found in horizontal flow. The main

exception is at low flow rate conditions. For vertical flow, static conditions only persist at very low flow

rates (i.e. <1 ft/sec; 0.3 meter/sec). For bottomhole conditions, this is usually only during shut-in of the

well. Above this velocity, there is enough agitation to produce a mixing of hydrocarbon, aqueous phases

and inhibitors. Therefore, between 1 and 30 ft/sec (0.3 to 30 meter/sec) in inhibited systems and 1 and 15

ft/sec (0.3 and 5 meter/sec) in non-inhibited systems corrosion rates and not usually affected greatly by

velocity. Only at flow rates above these ranges to corrosion rates increase rapidly with increasing

velocity due to removal of protective surface films.

2.3.12 Ratio of Hydrocarbons to Water

Conditions where a persistent liquid hydrocarbon phase is present can influence the tendency for

corrosion of steel and also may dictate the type of corrosion inhibition program to be most appropriately

utilized. Typically, conditions where the oil to water ratio (OWR) is > 2 generally result in less corrosion

of steel than those having lower ratios.

When considering this situation, the persistence of the liquid hydrocarbon on the steel surface is an

important factor. If experience shows that little or no oil persistence occurs, then the use of OWR less

than 2 in the program is suggested even though the actual value of OWR may be greater than 2. The

OWR ratio may also be determined as the reciprocal of the product of gas to oil ratio and water to gas

ratio.

2.3.13 Corrosion Allowance

In designing systems from materials such as steel, which can exhibit corrosion, it is common to take into

account an added factor of safety in terms of the Corrosion Allowance. The concept of Corrosion

Allowance involves the use of an increased thickness over that required for mechanical design to allow

for corrosion and metal loss that may take place during the project life or until replacement.

The magnitude of the Corrosion Allowance is dependent on the severity of corrosion expected and the

ability to mitigate corrosion usually by the use of corrosion inhibitors. The Corrosion Allowance in most

cases is < 0.12 inches (3 mm). However, in some particularly severe cases larger Corrosion Allowances

can be utilized.

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2.3.14 Service Life

Service Life is the period of useful service for a particular component. This is usually taken to be the

time required to achieve a corrosion metal loss equal to the Corrosion Allowance. Alternatively, Service

Life may be used to define the required Corrosion Allowance based on the assessment of corrosion

severity and inhibition performance and methods in the particular application.

2.3.15 Type of Flow

The flow conditions (i.e. static, stratified, turbulent, etc.) are dependent on the nature of the produced

gases and fluids and whether the flow is primarily horizontal (surface production) or vertical (subsurface

production). Horizontal flow is usually more prone to static and stratified conditions, which limits the

amount of mixing of oil and water phases at low flow rates. Vertical flow typically exhibits these types

of conditions only during period of shut-in of the well. (See Chapter 5 on Flow Modeling for more

information.)

2.3.16 Method of Inhibition

For horizontal flow systems the following types of inhibition method are commonly used:

No Treatment - The conditions may be essentially non-corrosive. This usually occurs under the

following conditions (a) very low acid gas (CO2 and H2S) partial pressures, (b) low amounts of water or

(c) a very persistent oil phase.

Continuous Inhibition - Inhibitor is continuously injected into the flow stream. This may be conducted

in both bottomhole and surface production systems. It is preferred where the flow velocity is greater than

10 ft/sec (3 meter/sec) or where the amount of water is high.

Batch Inhibition - Inhibitor is added in the flow system periodically in batch treatments usually

between two pigs. A strongly persistent filming inhibitor is usually used which can reduced corrosion

rates effectively during the period between batch treatments. This technique is usually effective where

the chloride concentration is high but the velocity is low. It is commonly used to supplement other

inhibition techniques.

Pigging - Pigging is the use of flowline pigs to assist in (a) application of batch inhibitors and (b)

removal of accumulated water, solids and other deposit in the flow system. In many applications,

pigging is required to get proper distribution of inhibition chemicals through the flow system. In cases

where flow velocity is low, pigging is used to remove water and deposits from the bottom of the pipe,

which can promote corrosion at this location.

For vertical flow systems the following types of inhibition method are commonly used:

No Treatment - The conditions may be essentially non-corrosive. This usually occurs under the

following conditions (a) very low acid gas (CO2 and H2S) partial pressures, (b) low amounts of water or

(c) very persistent oil phase.

Batch Inhibition - Inhibitor is added in the flow system periodically in batch treatments and usually

added to the tubing bore in a process where the fluids in the well bore are displaced with the inhibitor

and its carrier. A strongly persistent filming inhibitor is usually used which can reduce corrosion rates

effectively during the period between batch treatments. This technique is usually effective where the

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chloride concentration is high but the velocity is low. However, conditions of high temperature (>250 F;

120 C) and high flow rate generally limit the use of this technique.

Squeeze Treatment - Squeeze treatments are a modification of batch inhibition used for controlling

bottomhole corrosion. Instead of just displacing the tubing with inhibitor and its carrier fluid, the

squeeze treatments also forces the fluid under pressure into the surrounding formation. This has the

benefit of extending the duration between batch treatments in some wells. However, in other cases,

squeeze treatments can also interfere with the well‘s production by plugging the formation.

Continuous Inhibition - Inhibitor is continuously injected into the tubing at bottom of the string or

through a subsurface injection valve. The rate of injection is regulated to provide the inhibitor at a

required concentration to mitigate corrosion. While more costly and requiring more equipment than

batch inhibition, continuous inhibition has been shown to be more effective particularly in deeper high

temperature wells and at more severely corrosive conditions. At high flow rates, continuous inhibitor

injection may become costly and possibly ineffective.

2.3.17 Inhibition Efficiency

Inhibition Efficiency (IE) is a term that describes the efficacy of an inhibitor treatment in mitigating

weight loss corrosion. It is based on either laboratory or field data where inhibited and non-inhibited

corrosion rates are compared using the following equation:

IE = 100[(CRn - CRi)/CRn]

where

CRn = non-inhibited corrosion rate,

CRi = inhibited corrosion rate.

Values of IE near 100 percent represent conditions with maximum efficacy of the inhibitor treatment.

Conditions that affect IE include:

Inhibitor concentration.

Severity of corrosive environment.

Service temperature.

Solubility of inhibitor in aqueous phase.

Phase behavior of inhibitor and carrier fluid in service environment.

Persistence of inhibitor on metal surface.

Inhibitor screening is often used to compare the IE of different inhibitors formulations.

2.3.18 Measured pH

The PREDICT 6.0 system is enabled with a way to assess corrosion using the measured pH and the acid

gasses as input parameters. However, given the accurate, ionic pH prediction model built into PREDICT

6.0, it is recommended that users utilize the highly accurate pH predictions from PREDICT 6.0.

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2.3.19 Custom Wall Shear Stress

PREDICT 6.0 provides the incorporation of third party flow modeling results in the form of wall shear

stress and flow regime. As shown in the below screen shot, users can check the box for providing third

party results – the program will then override the in-built flow model and use these input parameters to

calculate corrosion rate predictions.

2.3.20 Gas Flow rate – Standard / Actual

In earlier versions of Predict, gas flow rate input data was limited to standard conditions, but now user

can provide gas flow rate data at standard as well as at actual conditions.

2.3.21 CO2 and H2S in aqueous phase (ppm)

In earlier versions of Predict, user was limited to provided acid gas data in the form of partial pressures

(as either vapor phase partial pressures or mol% concentration in vapor phase). Users can now provide

data in aqueous phase (ppm) as well and PREDICT 6.0 will estimate the equilibrium partial pressures for

given values of CO2 and H2S.

2.3.22 Scale Protection and Water Analyses options

Corrosion rate predictions can now be calculated based on user‘s preference of considering scale

protection. For more conservative predictions and analyses of high flowing conditions where scale

protection may not be relevant, users can choose to ignore the protective effect of scale products. Results

screen now shows whether system has FeS Scale,FeCO3 Scale or No Scale with saturation pH data.

Water analysis data can now be provided for both inlet and outlet conditions. Users can select the check

box to use the same water analyses data for both inlet and outlet. When this option is not checked the

system performs linear interpolation on data for each species to estimate concentration data at

intermediate points.

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2.3.23 Dew Point

PREDICT 6.0 provides users with the ability to provided the water data either in the form of an actual

liquid water flow rate at operating conditions or the system dew point. This data is used to estimate the

total water flow rate in the system (liquid + vapor) and this total water is then used to performed water

phase behavior predictions across the tubing/pipe length,.

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2.4 THE PREDICT 6.0 INTERFACE MENUS AND THE TOOLBAR

PREDICT 6.0 is equipped with an intuitive graphical interface that facilitates easy access to the

functionality of the program. The primary objective of the PREDICT 6.0 interface to give the user an easy-

to-use and powerful way of accessing the significant amount of information embodied in the program.

The user can perform a variety of tasks just at the click of a toolbar icon. The Toolbar appears minimized

by default and clicking on any of the options available shows a toolbar with a series of buttons as shown

in Figure 2.15

Figure 2.15 - PREDICT 6.0 Menu and Tool Bar – Home Menu

Most of the file operations, actions and utilities can be accessed from the Home menu.

Under the Home menu, the following list of buttons is available.

The New command allows the user to start a new PREDICT 6.0 consultation. You can work on

multiple consultations at a time. The panel on the left indicated the number of open consultations

and you can select the one you want to work with. The active consultation will be highlighted

and the name of consultation will appear on the title bar.

The Wizard command allows users to launch a wizard that guides the user through the various

steps of creating a consultation. PREDICT 6.0 Wizard will ask the user a series of questions to

setup a consultation.

The Import Socrates command allows user to import consultations saved using Socrates 9.0™.

The Open command allows the user to open other stored consultations of PREDICT 6.0. The

default extension for stored PREDICT 6.0 files is .prd.

The Close command closes the currently active consultation. Users will be prompted to save to

save consultations that have unsaved changes..

The Close All command closes all open consultations. Users will be prompted to save each

consultation that has changed since last opened.

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The Save command saves the current consultation to a file name provided by the user. It saves

the current environment configuration as well as the predicted corrosion rate and the pH and all

associated data provided.

The Save All command saves all the current consultations.

The Save As command saves the current consultation as a different file. The user is prompted to

provide a new file name.

The Save Copy As command saves a copy of the current consultation as a different file. The user

is prompted to provide a new file name.

The Save As Template command saves the current consultation as a template that can be used to

start the new consultation with the values of template instead of the default values.

The British toolbar icon lets the user switch back from Metric/SI units if the units have been

changed to SI. The default units in PREDICT 6.0 are British units.

The Metric toolbar icon lets the user switch from British units to Metric/SI. Please note that

Metric and SI systems of units are used interchangeably to refer to the same system of units in

PREDICT 6.0 and in this manual.

FIGURE 2.16 - PREDICT 6.0 MENU AND TOOL BAR – REPORTS MENU

The Reports menu provides access to the following options:

The Print button helps print reports of the consultation. Clicking on this button directly sends to

report to the default printer.

The Page Setup buttons helps configure the printer settings.

The Print Preview button shows print preview of consultation.

The Excel button provides the ability to export all the data to MS-Excel.

The PDF button provides the ability to save the report in PDF format so that it can be sent out

via email or saved for future reference.

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FIGURE 2.17 - PREDICT 6.0 MENU AND TOOL BAR – ANALYSIS MENU

The Analysis menu provides access to the following options:

The Profile icon provides a tool for calculating the Corrosion Rates & Estimating Water phase

behavior, not only at a single point in the piping system, but over user specified number of points

over the entire length of the pipe. Chapter 5 has more details about using this utility.

The MPA icon allows the user to perform concurrent multipoint analysis for parametric

perturbation effects for any of the relevant input parameters. For more details, refer Section 2.2.8.

The Expert MPS icon allows user to perform MPS by varying some critical parameters like

bicarbonates, chlorides, H2S partial pressure, CO2 partial pressure and temperature. For more

details, refer Section 2.2.7.

The MPS toolbar icon launches the Multipoint Sensitivity Analysis tool as described in Section

2.2.6.

FIGURE 2.18 - PREDICT 6.0 MENU AND TOOL BAR – TOOLS MENU

The Tools menu provides access to the following options:

The Cost toolbar icon lets the user perform a cost analysis for assessment of costs in using a

specific steel or evaluating the economics of an inhibitor program. The program determines an

annualized cost as well as an overall project cost based on present worth analysis.

The JIP Data icon provides the user access to real lab corrosion rate data obtained from 18 flow

loop tests. More details can be found in Section 2.2.12

The Preferences icon provides the user options to customize PREDICT 6.0 in terms of application

color theme, default file saving locations, template settings and default views. More details can

be found in Section 2.2.11.

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The Units Assistant icon allows the user to convert between British and Metric Units for most

commonly used flow and operational parameters.

Figure 2.18 - Predict 6.0 Menu and Tool Bar – Help Menu

The Help menu provides access to the following options:

The Contents, Search and Index toolbar icons provides the user access to various parts of the

extensive Help System. Users can either view the contents, search for a particular keyword or

navigate to the index. The Help system is shown below in Figure 2.17

The User Manual icon provides the user access to this User Guide in PDF Format. This user

guide is provided as a hard copy and a PDF version is also provided that can be launched by

using this toolbar button.

The About and Disclaimer icons provide additional details about the version, program

disclaimer and other pertinent information about PREDICT 6.0.

The License Information button provides one click access to license information, expiration

date, etc.

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Figure 2.17 - PREDICT 6.0 Help Window

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2.5 GENERAL NOTES ON CONSULTING PREDICT 6.0

PREDICT 6.0 has been completely re-designed to promote ease of use and provide advanced

analytical capabilities. The best approach to learning the PREDICT 6.0 interface is to explore the

program and its commands. The graphical interface is designed to be intuitive and can be

customized according to user preferences.

PREDICT 6.0 estimates in-situ pH and corrosion rate through utilization of a complex numerical

and heuristic model that incorporates data from extensive JIP data, literature, lab and field

experience spanning over 30 years of corrosion research. The model itself captures the

synergistic effects of different corrosive parameters and has been tested extensively on real-time

cases in order to calibrate the results of the program.

You can exit the program through choosing exit from the file menu or by choosing close after

clicking on the control-menu box on the left hand corner of every window.

The PREDICT 6.0 knowledge base embodies significant expertise in steel evaluation and corrosion

assessment. We believe that the program provides accurate results and consistent reasoning. However,

this program is advisory in nature and its conclusions, ought to be construed as such and nothing more.

The knowledge and rules are continually evolving entities and Honeywell will be updating the program

regularly to enhance its utility and accuracy.

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3. TECHNICAL DESCRIPTION OF PREDICT 6.0 MODEL

3.1 SYNOPSIS

One of the most fundamental issues in current day corrosion research is assessment of corrosion rates in

steels and determination of corrosivity of typical operating environments in oil and gas production. Such

an assessment requires an understanding of the role of primary environmental and metallurgical

variables and underlying mechanisms of corrosion. The PREDICT 6.0 system presents a novel

hierarchical approach to assess system corrosivity and prediction of corrosion rates in carbon steels in

production environments containing CO2 and/or H2S. In this Chapter, critical environmental parameters

that influence system corrosivity are identified and the effects of these parameters on corrosion are

examined. Modeling for synergistic assessment of system corrosivity as a function of relevant operating

parameters is presented and is accompanied by a description of the PREDICT 6.0 model.

3.2 INTRODUCTION

CO2/H2S corrosion in oil and gas production environments represents one of the most important areas of

corrosion research. It is so because of the criticality of the need to assess corrosive severity as a means

to ensure safe utilization of steels, which have wide application in just about every sphere of oil and gas

production and refining. Even though CO2/H2S corrosion and concomitant mechanisms have been areas

of significant work over the last thirty years, there still exists a need to accurately predict corrosivity of

CO2/H2S environments from a stand point of defining limits of use for carbon steels. Even though

numerous predictive models have been developed and are being developed1,2

, most of the available

predictive models tend to be either very conservative3 in their interpretation of results or focus on a

narrow range of parametric effects, thereby limiting the scope of the model‘s application in realistic

assessment of corrosivity and corrosion rates. Often times, data required by the models are often not

easily accessible or available to the operators who need to employ the model, thereby limiting the

applicability of the models to situations of reduced practical importance4,5

. In this context, the issue of

corrosivity assessment for carbon steels can be re-stated in terms of the following critical requirements

that formed the basis for the PREDICT 6.0 system development:

Develop a predictive model that utilizes commonly available operational parameters while

accounting for significant new insights from JIP data

Incorporate the effect of actual data from lab tests for H2S and CO2 corrosion in flowing conditions

Utilize existing lab/field data and theoretical models to obtain realistic assessments of corrosivity

and corrosion rates

Develop an ionic model to accurately characterize in-situ system pH

Develop a computational approach that integrates both numerical (JIP data) and mechanistic models

(first principles) with heuristic (field data and experience) information and knowledge about

corrosivity prediction.

The method adopted in the PREDICT 6.0 model captures both the effect of critical parameters on

corrosion rates and system pH as well as that of parameter interactions.

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The primary variables in corrosivity prediction in the PREDICT 6.0 system are the acid gases CO2 and

H2S that contribute to the typically acidic pH found in production environments. The PREDICT 6.0 model

uses the system pH as a central factor in modeling significant corrosivity mechanisms, including

contribution of multiple anions and cations, as well as in assessing the role of pH in corrosion product

dissolution and / or precipitation.

The model also uses the widely accepted de Waard - Milliams2 relationship for CO2 corrosion for a

determination of corrosion rates in CO2-based systems. However, the effective CO2 partial pressure in

the system is not based on the operating partial pressure but one obtained from the system pH. This rate

is further refined to account for the presence of H2S, corrosion products, temperature effects etc.

A technical description of different corrosivity modeling parameters and their effects is given in ensuing

sections of this Chapter. The underlying idea here is to capture a prediction model within the PREDICT

6.0 system to accurately represent the state-of-the-art in theoretical analyses as well as parametric

correlations based on lab and field data. The PREDICT 6.0 system‘s development has been guided by

comparison with data from actual field conditions in an effort to compare system predictions6 with field

observations.

An important concept in the PREDICT 6.0 model is the role of superposition of different parameters. Such

super-positioning requires a clear understanding of independent parameter effects and also on how

corrosion rate progresses when subjected to the effects of two or more variables. While the current

prediction model is primarily concerned with environmental constituents and their effects of corrosion, it

is also important to recognize the significant role of metallurgy in fashioning appropriate corrosion

behavior. Influence of compositional and alloying elements has been chronicled but has hitherto not

been rigorously studied in assessing resistance to system corrosivity and a brief discussion of

metallurgical factors in corrosivity determination is provided elsewhere in this Chapter.

3.3 CO2/H2S-BASED CORROSION: TECHNICAL BACKGROUND AND LITERATURE REVIEW

CO2-based corrosion has been one of the most active areas of research, with several predictive models

for carbon steel corrosion assessment. These efforts range from a predictive model that begins with CO2

corrosion2,3

to models that focus on specific aspects of the corrosion phenomena (such as flow-induced

corrosion or erosion corrosion)4,5

to models that empirically relate corrosion rates to gas production and

water production rates7. Crolet et al.

8 use the physical chemistry of the corrosive medium as the key

notion and take into account ionic strength, pH and specific ionic species as relevant factors. Other

relevant efforts include those by Ikeda et al. 9

that look at the influence of H2S and O2 on CO2-based

corrosion as well as those by Adams et al.10

. Many of these efforts suffer from significant drawbacks in

that,

They focus on a narrow range of parametric effects, for e.g., there is relatively little published

information on the effects of H2S in production systems and on how sulfide scaling can affect the

CO2 corrosion process

Some models focus just on one component of corrosivity, such as erosional effects, wall shear stress

effects or flow effects and have opted to ignore effects of chemical species (factors such as pH, H2S,

CO2 etc.)

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Other models totally rely on lab data for predictive modeling, with the consequence that the

simplifying assumptions made in developing laboratory models often lead to results that can be far

removed from what is observed in the field.

The current model integrates lab data and field experience within the framework of relevant controlling

parameters that are most prominent in oil and gas production. It is important to realize that while arcane

theoretical models are interesting from an academic stand point, the controlling parameters in a model

must also represent data easily available to oil and gas production personnel. The current model

attempts to integrate principles hitherto delineated in developing the PREDICT 6.0 model.

While there have been several studies focusing on the exact mechanism of metal dissolution in CO2

containing waters, the efforts of de Waard and Milliams and others2,3,9

present a commonly accepted

representation wherein anodic dissolution of iron is a pH dependent mechanism as given by Bockris2,

the cathodic process is driven by the direct reduction of undissociated carbonic acid. These reactions

can be represented as3,

Fe ----------> Fe++

+ 2e- (Anodic reaction)

H2CO3 + e-----> HCO3

- + H (Cathodic reaction)

The overall corrosion reaction can be represented as,

Fe + 2H2CO3 ---> Fe++ + 2 HCO3- + H2

The build up of the bicarbonate ion can lead to an increase in the pH of the solution till conditions

promoting precipitation of iron carbonate are reached, leading to reaction given below:

Fe + 2HCO3- ---> FeCO3+ H2O+CO2

Iron carbonate solubility, which decreases with increasing temperature, and the consequent precipitation

of iron carbonate is a significant factor in assessing corrosivity. The charge transfer controlled reaction

involving carbonic acid and carbon steel (or Fe) can be represented in terms of the concentration or

partial pressure of dissolved CO2 in the medium to arrive at a corrosion rate equation that incorporates

the order of the reaction and an exponential function that approximates for Henry‘s reaction constant‘s

temperature dependence. This corrosion rate equation is given as2,

log (Vcor) = 5.8 - 1710/T + 0.67 log (pCO2) ------ (1)

Where,

Vcor = corrosion rate in mm/yr

T = operating temperature in K

pCO2 = partial pressure of CO2 in bar

The corrosion rate obtained by equation (1) has typically been often seen as the maximum possible

corrosion rate without accounting for iron carbonate scaling. A nomogram representing eq. (1) is given

in Figure 3.12, which also includes a scale factor to account for the formation of protective carbonate

films that lead to a reduced corrosion rate at higher temperatures.

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Figure 3.1: CO2 Corrosion Nomogram

The above correlation describes CO2-based corrosion. There have been other significant efforts to

demonstrate the effects of other environmental variables such as pH, H2S, chlorides, bicarbonates,

water/gas/oil ratios, velocity etc. Effects of H2S on corrosion rates in the laboratory have been studied

and presented by Videm11

et al., and Ikeda9 et al. Ikeda‘s work indicates that the preferential formation

of an Iron sulfide film can decelerate the corrosion rate, especially at temperatures above 20 C and

extending up to 60 C. Above 150 C, the corrosion reaction falls back to the standard CO2-based

corrosion with an FeCO3 film that is more stable than the FeS film. Videm‘s work supports the theory

that even small amounts of H2S can provide instantaneous protection at temperatures in the range 70-80

C.

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Lotz et al. 12

have chronicled the role of the hydrocarbon condensate in providing corrosion mitigation in

specific production systems. The role of the type of oil or gas condensate is important from the stand

point of accurate assessment as reported by Choi et al13,14

. Other studies evaluating effects of critical

parameters such as pH and velocity on CO2 corrosion include those by Dugstad15

as well as Lotz16

.

Other predictive models also include those by Gunatlun17

and Bonis et al18

wherein a combination of the

parameters discussed herein along with electro-chemical considerations have been utilized to arrive at

the corrosion rate.

The primary objective of the corrosivity prediction model described in this Chapter is to address the need

of developing a predictive method that would synthesize different parametric relationships based on

information from literature, lab research/data and practical experience/expertise. It has often been

observed that lab data and the ensuing models represent poor and often inadequate simulation of field

conditions19

. It is also necessary to understand that field data is typically sparse and can be negated by

other production data. The need to integrate field data/experience and laboratory models stems from the

fact that the lab data can provide significant pointers and trends that can be used in conjunction with

field data and experience. The idea is to develop a methodology that can integrate analytical and

heuristic models.

To this end, this PREDICT 6.0 system mirrors other successful development efforts undertaken by

Honeywell in the areas of evaluation of CRAs and cracking in steels20,21

. The central theme is to

develop a computer program that can bring together different types of modeling knowledge to provide a

realistic solution to the significant question of predicting corrosion rates in typical production

environments.

3.4 PREDICT 6.0 MODEL DESCRIPTION

The first step in corrosivity determination is computation of the system pH, since it is the hydrogen ion

concentration that drives the anodic dissolution. Further, the role of pH in promoting or mitigating CO2-

based corrosion has been extensively chronicled22,19

. For production environments, where it is the

dissolved CO2 or H2S that contribute significantly to a suppressed pH, the pH can be determined as a

function of acid gas partial pressures, bicarbonates, organic acids and temperature, as well as relevant

anions and cations. A detailed description of the PREDICT 6.0 pH prediction model is given Section

3.4.10.

Once the system pH is determined, the effective CO2 partial pressure can be determined from as,

Log(pCO2-eff) = (C1 - pH) / 2 ---------------- (2)

where pCO2-eff is the effective partial pressure of CO2 in a production system that can produce the

prevalent level of hydrogen ion concentration.

The effective CO2 partial pressure from (2) can be used in Equation (1) to determine an initial corrosion

rate for CO2-based corrosion. The corrosion rate so obtained is modified to account for the formation of

a FeCO3 film (Fe3O4 at higher temperatures) whose stability varies as a function of the operating

temperature. The scale correction factor shown in Figure 3.1 is used to determine the initial corrosion

rate from the nomogram in Figure 3.12. It is generally estimated that this corrosion rate presents a

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maximum corrosion rate even though it has been reported that the rate computed by the nomogram are

reached or exceeded in systems with high flow rates. It is important to recognize that this corrosion rate

has to be modified to account for the effect of other critical variables in the system. Further, this rate

does not indicate modality (general or localized) but rather, represents the maximum rate of attack.

PREDICT 6.0 also calculates the saturation pH (pHSat) of FeCO3 and FeS using the electroneutrality

equations given by Crolet & Bonis. The calculation of pHSat is important in that pH, pHSat - pHBulk ,

can be used to determine if an environment is corroding or scaling. A positive value in pH, i.e., the

saturation pH of a particular compound is greater than the bulk pH, is an indication that the system is

corroding. A negative value in pH, i.e., the saturation pH of a particular compound is lesser than the

bulk pH, is an indication that the system is scaling.

As mentioned earlier, it is necessary to superposition the effects of other critical system parameters. In

addition to the system pH, these include,

H2S partial pressure

Maximum operating temperature

Dissolved chlorides

Gas to oil ratio

Water to gas ratio/water cut

Oil type and its persistence

Elemental sulfur/aeration

Type of flow and flow regime

Wall Shear Stress and fluid velocity

Inhibition type and efficiency

The following sections discuss the effects of these parameters on corrosivity and provide information as

to how it is critical to examine the parameter interactions prior to capturing the synergistic effects of

these parameters on corrosion.

3.4.1 Role of H2S

Oilfield production environments, in recent years, have been characterized by increasing presence of H2S

and related corrosion considerations. Even though H2S is probably the most significant concern in

current day corrosion and cracking evaluation, the role of H2S in corrosion in steels has received much

less attention when compared to the widely studied CO2 corrosion.26

However, H2S related corrosion

and cracking has remained one of the biggest concerns for operators involved in production because of

the significance of H2S related damage27

.

The current modeling effort, in addition to its contribution in pH reduction, H2S has a threefold role:

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At very low levels of H2S (< 0.01 psia), CO2 is the dominant corrosive species, and at temperatures

above 60 C, corrosion and any passivity is a function of FeCO3 formation related phenomenon and the

presence of H2S has no realistic significance.

In CO2 dominated systems26,28

, presence of even small amounts of H2S (ratio of pCO2/pH2S > 200),

can lead to the formation of an iron sulfide scale called mackinawite at temperatures below 120 C.

However, this particular form of scaling, which is produced on the metal surface directly as a function of

a reaction between Fe++

and S—

is influenced by pH and temperature27

. This surface reaction can lead to

the formation of a thin surface film that can mitigate corrosion. The JIP data included in PREDICT 6.0

provides a laboratory basis to characterize the stability and formation of mackinawite in sour systems.

(3) In H2S dominated systems (ratio of pCO2/pH2S < 200), there is a preferential formation of a

meta-stable sulfide film in preference to the FeCO3 scale; hence, there is protection available due to the

presence of the sulfide film in the range of temperatures 60 to 240 C. Here, initially it is the

mackinawite form of H2S that is formed as a surface adsorption phenomenon. At higher concentrations

and temperatures, mackinawite becomes the more stable pyrhotite. However, at temperatures below 60

C or above 240 C, presence of H2S exacerbates corrosion in steels since the presence of H2S prevents

the formation of a stable FeCO3 scale.9, 29

Further, it has been observed that FeS film itself becomes

unstable and porous and does not provide protection. Also, the scale factor applicable for CO2 corrosion

with no H2S (shown in Figure 3.1) becomes inapplicable. Even though there is agreement amongst

different workers that there is a beneficial effect of adding small amounts of H2S at about 60 C, Ikeda et

al.9 and Videm et al.

11 present divergent results at higher concentrations and higher temperatures.

The effect of H2S adopted in the PREDICT 6.0 model reflects work published by T. Murata et al.29

for

CO2 dominated systems. Figure 3.229

shows the combined effects of temperature and gas composition

on corrosion rate of carbon steels. Figure 3.39 shows the effect of varying degrees of H2S contamination

on CO2 corrosion. It is to be noted that the role of H2S in CO2 corrosion is a complex issue governed by

film stability of FeS and FeCO3 at varying temperatures and is an area further active research by

Honeywell.

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Figure 3.2: Effect of gas composition and temperature on corrosion rate

3.4.2 Temperature Effects

Temperature has a significant impact on corrosivity in CO2/H2S systems. Corrosion rate as a function of

different levels of CO2 and temperature are given in Figure 3.42. It has to be noted that once the

corrosion products are formed, there is a significant mitigation in corrosivity. It is also apparent that the

carbonate film is more stable at higher temperatures and affords greater protection at higher

temperatures. Figure 3.4 also shows that at temperatures beyond 120 C, corrosion rate is almost

independent of the CO2 partial pressure of the system. The carbonate film may, however, be weakened

by high chloride concentrations or can be broken by high velocity. In H2S dominated systems, because

of the fact that no carbonate scale may be formed and that the FeS film becomes porous and unstable at

temperatures beyond 120 C, significant localized corrosion may be observed.

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Figure 3.3: Effect of H2S and temperature on corrosion rate in pure iron

3.4.3 Chlorides

Produced water from hydrocarbon formations typically contains varying amounts of chloride salts

dissolved in solution. The chloride concentration in this water can vary considerably, from zero to few

ppm for condensed water to saturation in formation waters having high total dissolved salts/solids

(TDS). In naturally deaerated production environments, corrosion rate increases with increasing

chloride ion content over the range 10,000 ppm to 100,000 ppm30

. The magnitude of this effect

increases with increasing temperature over 60 C (150 F). This combined effect results from the fact

that chloride ions in solution can be incorporated into and penetrate surface corrosion films which can

lead to destabilization of the corrosion film and lead to increased corrosion. This phenomenon of

penetration of surface corrosion films increases in occurrence with both chloride ion concentration and

temperature.

3.4.4 Bicarbonates

Bicarbonates in the operating environment have a significant impact on corrosion rates. On one hand,

high levels of bicarbonates can provide higher pH numbers leading to corrosion mitigation even when

the partial pressures of CO2 and H2S are fairly high. There is a natural inhibitive effect of presence of

bicarbonates which can be present in substantial quantities in formation waters (up to 20 meq/l)31

.

Condensed water in production streams typically contains no bicarbonates. Bicarbonates affect both the

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ionic strength and system pH and hence play a critical role in both formation of protective scales and

supply of protons that contribute to increased corrosion rates.

Figure 3.4: Corrosion rate as a function of temperature and CO2 pressure

3.4.5 Wall Shear Stress and Liquid Velocity

In any multiphase flowing system, different flow regimes are manifested as a function of how the vapor

and liquid phases mix. Such flow regimes give rise to different types of fluid forces, and effect different

levels of wall shear. Such wall shear stress has a significant impact on removal of corrosion films, on

mass-transfer coefficient (most turbulent flows operate in mass transfer control rather than activation

control for corrosion) and consequently increased corrosion at high wall shear stress levels. The topic of

multiphase flow modeling is complex enough to merit a complete chapter, and a detailed description of

the flow modeling module in PREDICT 6.0 is given in Chapter 4.

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Effect of wall shear stress on corrosion rates, in PREDICT 6.0, stems from the extensive JIP data

generated in the Joint Industry Project on Prediction and Assessment of Corrosivity of Multiphase

CO2/H2S systems. The methodology for such corrosion modeling may be captured as,

- Perform flow modeling to compute wall shear stress (WSS) at given condition.

- Calculate the base corrosion rate for steels (CRBase) from computed wall shear stress.

- Obtain the CO2 (CFCO2), temperature (CFTemp), and chloride (CFCl) correction factors

from data provided by user.

- Base corrosion rate of steels (CRBase) is multiplied by CO2, temperature, and chloride

correction factors to get the final H2S corrosion rate.

Please see Section 3.4.9 for further details on this topic.

Under conditions not covered by the JIP data, PREDICT 6.0 utilizes a model from literature to account for

fluid flow effects in terms of fluid velocity. Fluid flow velocities affect both the composition and extent

of corrosion product films. Typically, high velocities (> 4 m/s for non-inhibited systems) in the

production stream leads to mechanical removal of corrosion films and the ensuing exposure of the fresh

metal surface to the corrosive medium leads to significantly higher corrosion rates. Corrosion rate as a

function of flow velocity and temperature is shown in Figure 3.515

.

In multiphase (i.e. gas, water, liquid hydrocarbon) production, the flow rate influences the corrosion rate

of steel in two ways. First, it determines the flow behavior and flow regime. In general terms, this is

manifested as static conditions (i.e. little or no flow) at low velocities, stratified flow at intermediate

conditions and turbulent flow at higher flow rates. One measure which can be used to define the flow

conditions is the superficial liquid velocity.

Velocities less than 1 m/s are considered static. Under these conditions corrosion rates can be higher

than those observed under moderately flowing conditions. This occurs because under static conditions,

there is no natural turbulence to assist the mixing and dispersion of protective liquid hydrocarbons or

inhibitor species in the aqueous phase. Additionally, corrosion products and other deposits can settle out

of the liquid phase to promote crevice attack and underdeposit corrosion.

Between 1 and 3 m/sec, stratified conditions generally still exist. However, the increased flow promotes

a sweeping away of some deposits and increasing agitation and mixing. At 5 m/sec, corrosion rates in

non-inhibited applications start to increase rapidly with increasing velocity.31

Data shown in Figure 3.631

demonstrates the effects of velocity on corrosion rate for both inhibited and non-inhibited systems. For

inhibited applications, corrosion rates of steel increase only slightly between 3 to 10 m/sec, resulting

from mixing of the hydrocarbon and aqueous phases. Above about 10 m/sec, corrosion rates in inhibited

systems start to increase due to the removal of protective surface films by the high velocity flow.

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Figure 3.5: Corrosion rate as a function of velocity and temperature

Flow related effects on corrosivity have been linked to the wall shear stress developed and is an area of

intense research in the community32

. Flow induced corrosion is a direct consequence of mass and

momentum transfer effects in a dynamic flow system where the interplay of inertial and viscous forces is

responsible for accelerating or decelerating metal loss at the fluid/metal interface. Another relevant

aspect of flow or velocity induced corrosion is erosion corrosion33

and refers to the mechanical removal

of corrosion product films through momentum effects or through impingement and abrasion. Guidelines

for velocity limits with respect to erosional considerations are given in API-14E in terms of the density

of the fluid medium.34

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Figure 3.6: Effect of gas velocity on corrosion rate

3.4.6 Importance of Water/Gas/Oil ratios

The PREDICT 6.0 model classifies systems as oil dominated or gas dominated on the basis of the gas/oil

ratio (GOR) of the production environment. If the environment has a GOR < 890 m3/m

3 (5000 scf/bbl in

English units)35

, the tendency for corrosion and environmental cracking is often substantially reduced.

This is caused by the possible inhibiting effect of the oil film on the metal surface, which effectively

reduces the corrosivity of the environment. However, the inhibiting effect is dependent on the oil phase

being persistent and acting as a barrier between the metal and the corrosive environment. The

persistence of the oil phase is a strong factor in providing protection, even in systems with high water

cuts. In oil systems with a persistent oil phase and up to 45 percent water cut, corrosion is fully

suppressed, irrespective of the type of hydro-carbon12

. Relative wettability of the oil phase versus the

water phase has a significant effect on corrosion36

. Metal surfaces that are oil wet show significantly

lower corrosion rates37

.

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The PREDICT 6.0 model described in this Chapter provides for a significant reduction in the corrosion

rate (up to a factor of 4) based on the type of oil phase being persistent, mildly persistent and not

persistent. However, the degree of protection can be quantified only as a function of water cut and

velocity. The persistence determination is a more complex task and requires knowledge of the kerogen

type and hydrocarbon density. It is important to understand the type of crude oil in terms of the organic

compounds that make up the crude to determine wettability effects. Figure 3.7 shows data that relates

the acid number of the crude to oil wettability and Figure 3.8 shows corrosion rate as a function of

produced water content for different crude oil/produced water mixtures36

. While the effect of

persistence of the oil medium is significant on corrosion rates, it is even more difficult to quantify

precise compositional elements of an oil medium that contribute to wettability and persistent oil film

formation. Such quantification is possible by rigorous laboratory testing of different actual,

uncontaminated (read deaerated) production water samples, so as to determine the extent of protection.

Figure 3.7: Effect of acid number on crude oil wettability

In oil systems the water cut acts in synergy with the oil phase to determine the level of protection from

the hydrocarbon phase. However, at very low water cuts (less than 5 percent), corrosive severity of the

environment is lessened due to the absence of an adequate aqueous medium required to promote the

corrosion reaction.

In gas dominated systems, there are two measures to evaluate availability of the aqueous medium. If the

operating temperature is higher than the dew point of the environment, no condensation is going to be

possible and will lead to highly reduced corrosion rates. Corrosion under condensing conditions (i.e.,

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operating temperature less than the dew point) is a function of the rate of condensation and transport of

corrosion products from the metal surface.38

If the total water in a condensing system as measured by

the Water to Gas Ratio is less than 11.3m3/Mm

3 (2 BBL water/MSCF gas), corrosivity is substantially

reduced.

Figure 3.8: Effect of changing crude oil type on corrosion rate as a function of water content

3.4.7 Oxygen/Sulfur

Presence of oxygen significantly alters the corrosivity of the environment in production systems.

Oldfield39

has chronicled how presence of oxygen can significantly increase corrosion rates due to

acceleration of anodic oxidation. While corrosion rate increases with oxygen, rate of oxygen reduction

as a cathodic reaction is further exacerbated by:

Increase in operating temperature

Increased fluid flow leading to increased mass flow of oxygen to the metal surface

Increasing oxygen concentration

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Data showing increases in corrosion rate as a function of oxygen concentration for differing

temperatures is shown in Figure 3.939

. Corrosion rates for different flow velocities and oxygen levels as

a function of temperature is shown in Figure 3.1039

. Presence of elemental sulfur is similar to that of

free oxygen since elemental sulfur also acts as a strong oxidizing agent.

3.4.8 Inhibition/Inhibition Effectiveness

Appropriate inhibition is a critical criterion for effective use of carbon steels in corrosive production

systems. Inhibition has been typically found to be viable in flows with velocity in the range 0.3 - 10 m/s.

Requirements for the type of inhibitor and the method of delivery depend on the type of system

(production tubing or horizontal flow lines) to be inhibited. Inhibition Efficiency (IE) describes the

efficacy of an inhibitor treatment in mitigating weight loss corrosion and is an important factor in

assessing corrosivity. It is based on either laboratory or field data where inhibited and non-inhibited

corrosion rates are compared using the following equation:

IE = 100[(CRn - CRi)/CRn]

Where

CRn = non-inhibited corrosion rate,

CRi = inhibited corrosion rate.

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Figure 3.9: Effect of oxygen concentration as a function of temperature on corrosion

Values of IE near 1.0 represent conditions with maximum efficacy of the inhibitor treatment. Conditions

which affect IE include:

1. Inhibitor concentration.

2. Severity of corrosive environment.

3. Service temperature.

4. Solubility of inhibitor in aqueous phase.

5. Phase behavior of inhibitor and carrier fluid in service environment.

6. Persistence of inhibitor on metal surface.

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The PREDICT 6.0 model evaluates inhibition efficacy on the basis of velocity, hydrocarbons to water ratio

and dissolved chloride levels. The method of delivery (batch, continuous, pigging etc.) is also an

important factor in determining appropriateness of inhibition for a given set of operating conditions.

Figure 3.10: Effect of oxygen concentration as a function of temperature on corrosion

3.4.9 Incorporation of H2S Corrosion Data from JIP

PREDICT 6.0 has incorporated PANDA (Prediction Assessment of Corrosivity of Multiphase CO2 / H2S

Environments) report data; data obtained in a joint industry sponsored program conducted by

Honeywell. This report encompasses over 18 flow loop tests conducted over an eighteen month period

for different environments. Data generated in this report indicates partial pressure CO2, chloride content,

shear stress and temperature plays an important role on H2S corrosion behavior.

Data detailed in PANDA report indicates that:

- Corrosion rate was lower at higher levels of H2S at ambient temperature, indicating

benefit of higher levels of H2S.

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- Corrosion rate for impingement and reservoir specimens were higher than that for laminar

coupons in all cases.

- Corrosion rate increased with increase in velocity.

- Higher corrosion rates were observed with higher chlorides.

- No effect of velocity was seen at low levels of H2S, indicating possible scaling of the

coupons.

PREDICT 6.0 uses the following methodology to calculate/ predict H2S corrosion rate for steels:

- Perform flow modeling to compute wall shear stress (WSS) at given condition.

- Calculate the base corrosion rate for steels (CRBase) from computed wall shear stress.

- Obtain the CO2 (CFCO2), temperature (CFTemp), and chloride (CFCl) correction factors

from data provided by user.

- Base corrosion rate of steels (CRBase) is multiplied by CO2, temperature, and chloride

correction factors to get the final H2S corrosion rate.

The final H2S corrosion rate predicted is represented by the following relationship:

CRFinal = CRBase x CRCO2 x CRTemp x CRCl

CRBase: Base corrosion rate

CRCO2: CO2 correction factor

CRTemp: Temperature correction factor

CRCl: Chloride correction factor

3.4.10 Updated pH Prediction Model

The importance of pH determination in corrosion field has been well recognized, because pH is one of

the most critical parameters in corrosivity determination. PREDICT 6.0 calculate the pH by using the

Brönstead concept 63

. The pH calculation involves H+, HCO3

-, CO3

-, H2S, HS

-, S

-, OH

-, acetate and

formate. The effects of common anions and cations species were taken into consideration thought their

influence on dissociation equilibrium constants. The pH of an aqueous solution is generally defined by

following equation:

pH = -log aH

+

= -log γ H+m H

+

aH+: Activity of hydrogen ion

γ H+: Activity coefficient

m H+: Hydrogen ion concentration

For systems containing carbon dioxide and hydrogen sulfide, the following ionic balance has been

developed:

[H+] = [HCO3

-] + 2 [CO3

-2] + [HS

-] + 2 [S

-2] + [OH

-] – CHCO3

- – 2 CHS

-2 – CHCO3

- - 2 CS

-2

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The ions in brackets are equilibrium concentrations and were computationally determined by following

dissociation process.

Equilibrium concentration of carbonate ion,

KH

CO2 + H2O H2CO3

K1

H2CO3 H+ + HCO3

-

K2

HCO3- H

+ + CO3

-2

[H2CO3]

KH =

[pp CO2]

[H+] [HCO3

-]

K1 =

[H2CO3]

[H+] [CO3

-2]

K2 =

[HCO3-]

Further simplifying the above equations gives,

[pp CO2] K1K2KH

[CO3-2

] =

[H+]

2

Which,

KH – Henry‘s law constant

K1 – First dissociation constant of CO2

K2 – Second dissociation constant of CO2

Equilibrium concentration of sulfide ion,

KH

H2S + H2O H2S

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K1

H2S HS- + H

+

K2

HS- S

-2 + H

+

[H2S]

KH =

[pp H2S]

[H+] [HS

-]

K1 =

[H2S]

[H+] [S

-2]

K2 =

[HS-]

Further simplifying the above equations gives,

[pp H2S] K1K2KH

[S-2

] = .

[H+]

2

Which,

KH – Henry‘s law constant

K1 – First dissociation constant of H2S

K2 – Second dissociation constant of H2S

Dissociation of water,

KW

H2O H+ + OH

-

KW = [H+] [OH

-]

Thus, the pH of solution with the presence of CO2 and H2S can be obtained by solving above equations.

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3.4.11 Pitting Probability Model

Often, rather than uniform corrosion, pitting is the main cause of failure in production and transport of

oil and gas. Pitting is a localized form of corrosion on a metal surface, which rapidly attacks or

penetrates at small discrete spots in the metal surface. The rate of penetration may be 10 to 100 times

that of general corrosion. It is considered to be more dangerous than uniform corrosion damage because

it is more difficult to detect, predict and prevent. Pitting depends on the characteristics of the metals,

amount of CO2, amount of H2S, pressure, temperature, composition of aqueous streams, and pH.

Pitting/ localized corrosion involves at least two main steps/stages, initiation, and propagation. A

protective iron carbonate scale may form on the metal surface under the right environment as a by

product of corrosion process. Unfortunately, any damage to this film may be one of the ways to initiate

localized corrosion. In some cases localized corrosion is initiated but it does not propagate. Recently,

Ohio University demonstrated that pits will propagate only if the conditions are just right (grey zone

criterion) 64

.

Throughout the experiments detailed in Ref 64, the criteria for the likelihood of localized corrosion were

determined. Localized corrosion occurred only when partially protective films were formed; whereas

under film-free conditions or formation of fully protective films, only uniform corrosion is expected.

Therefore, super saturation level is critical to predict likelihood of localized corrosion. Super saturation

level less than 1 means the solution is under saturated; and super saturation level greater than 1 means

the solution is super saturated. At levels close to saturation point (close to 1), materials tend to be locally

and highly attacked, thus increasing the likelihood of localized corrosion. Criteria for Super saturation

may be characterized as:

If SS << 1 or SS >> 1 uniform corrosion

If 0.5 ≤ SS ≤ 3 localized corrosion is likely

The iron carbonate super saturation level (SS) is defined as follows:

spK

COFeSS

]][[ 2

3

2

Where,

[Fe2+

] – Equilibrium concentration of ferrous ion in mol/l

[CO32-

] – Equilibrium concentration of carbonate ion in mol/l

Ksp – Solubility Product of iron carbonate

Other than the ―Grey Zone‖ theory, it is believed that the Cl- concentration tends to facilitate pitting. It is

evident that steels become more susceptible to localized corrosion as the chloride concentration

increases. Repassivation and Corrosion potentials were used to determine the minimum concentration of

chloride ions necessary for pitting to initiate and propagate. Steels should be immune/ less likelihood to

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pitting in deaerated/ low chloride ions solutions since the repassivation potential is more active than

corrosion potential. As the chloride concentration increases, the difference between repassivation and

corrosion potentials is reduced which increase the likelihood of localized corrosion. Once corrosion

potential is above the repassivation potential, the likelihood of localized corrosion is high. And it‘s

indicated that if a pit nucleated, it would continue propagating65,66

.

As mentioned above, if the system condition falls into the ―Grey Zone‖ or exceeds the critical Cl-

concentration, localized propagation is expected. Hence, the risk of localized corrosion can be predicted

through super saturation and Cl- concentration level.

3.4.12 Summary

The corrosion rate predicted in the current model can be represented in terms of three broad rules that

guide the computer model‘s decision making:

1. Effect of fundamental system variables such as CO2, H2S, pH, temperature, and fluid flow (flow

regime, wall shear stress, velocity) on corrosion rate.

2. Effect of parameter interactions on corrosivity, such as, influence of temperature on the carbonate or

sulfide film stability. Or flow effects on corrosion products and the ensuing loss of protective films

as a function of velocity, temperature, acid gases and pH.

3. Effects of system modifiers such as oil film persistence (or lack of it) or the crude type, water cut,

dew point, aeration and inhibition.

Corrosion rate, thus predicted, incorporates the synergy of effects of all the critical system variables and

provides a more realistic estimation of corrosivity than what would be available with conservative

theoretical models that focus on a limited number of parameters. The significance of the reasoning in

PREDICT 6.0 model stems from the fact that the decisions made synthesize different types of corrosion

knowledge:

Theoretical mechanistic models that provide effects of different parameters, including system

thermodynamics, phase behavior, speciation, solubility etc.

Data from extensive laboratory testing (JIP) that provide a numerical model for correlating wall

shear stress and corrosion rates

Data from laboratory tests that provide insight on parametric correlations and trends about

parametric effects, and

Experience-based heuristics that facilitate proper interpretation of data from lab and field.

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4. FLOW MODELING IN PREDICT 6.0

4.1 OVERVIEW

Multiphase systems present an imposing challenge from a standpoint of corrosion evaluation and

prediction because of the need to synergistically capture the role of important environmental, flow and

metallurgical variables and underlying mechanisms of corrosion. In this chapter, we focus on modeling

fluid flow in order to assess wall shear stress and pressure drop in multiphase systems.

4.2 INTRODUCTION

Proper modeling of multiphase flow requires an understanding of the physical system. When co-current

flow of multi-phases occurs, the phases take up a variety of configurations, known as flow patterns52

.

The particular flow pattern depends on the conditions of pressure, flow and channel geometry. In

corrosion prediction and assessment in oil and gas wells, the flow pattern or successive flow patterns

that would exist in the well and shear stress at the wall are essential. The flow modeling module in

PREDICT 6.0 helps the user in predicting the flow pattern and assessing the shear stress and pressure drop

for various flow regimes depending on the flow parameters, thus helping the user in assessing the

effective corrosion rate.

4.3 VERTICAL FLOW

PREDICT 6.0 uses the flow map proposed by Kabir and Hasan52

. The flow map is developed based on

theoretical principles and is verified using experimental data. The model is found to have a better

accuracy in calculation of flow regime, liquid hold-up and pressure drop, over other models. As per

Kabir and Hasan, the four flow patterns that occur in a vertical flow are - bubbly, slug, churn and

annular - shown in Figure 4.1.

At low gas flow rates, the gas phase tends to rise through the continuous liquid medium as small discrete

bubbles giving rise to the name, bubbly flow.

As the gas flow rate increases the smaller bubbles begin to coalesce forming larger bubbles. At

sufficiently high gas flow rates, the agglomerated bubbles become large enough to occupy almost the

entire pipe cross-section. These large bubbles, known as ‗Taylor bubbles‘, separate the liquid slugs

between them. The liquid slugs, which usually contain smaller entrained gas bubbles, gives the name of

the flow regime.

At still higher flow rates the shear stress between the ‗Taylor‘ bubble and the liquid film increases,

finally causing a breakdown of the liquid film and the bubbles. The resulting churning motion of the

fluids give rise to the name of this flow pattern.

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The final flow pattern, annular flow, occurs at extremely high gas flow rates which causes the entire gas

phase to flow through the central portion of the tube. Some liquid is entrained in the gas core as droplets

while the rest of the liquid flows up the wall through the ‗annulus‘ formed by the tube wall and the gas

core.

Figure 4.1 - Flow Patterns in Vertical Concurrent Two Phase Flow

A brief summary of the model used for calculation of flow pattern, liquid hold-up and pressure drop is

given below:

Summary of the Model

4.3.1. Bubbly Flow:

Transition Criteria: V V V V Vsg sl t t tT 0 429 0 357. . or

or and E V D

gg m

l g

l

m

l

052 4 681 12 0 48

0 50 6 0 08

. .. .

.. .

Void Fraction:

EV

C V Vg

sg

m t

0

CD

Dc

t0 12 0 371

. .

Pressure Drop: dP

dzf V

g Df

m m m

c

2 2

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4.3.2. Slug Flow:

Transition Criteria: V V Vsg sl t 0 429 0 357. . and

V V Vsg g l sl l sl

2 2 2171 232 50 . log . if or

V V Vsg g l sl l sl

2 2 20 00673 50 .1.7

if

Void Fraction:

EV

C V Vg

sg

m tT

1

CD

Dc

t1 12 0 90

. .

Pressure Drop: dP

dz

f V E

g Df

m m m g

c

2 12

4.3.3. Churn Flow:

Transition Criteria:

V

gsg

l g

g

31 2.

0.25

and

V V Vsg g l sl l sl

2 2 2171 232 50 . log . if or

V V Vsg g l sl l sl

2 2 20 00673 50 .1.7

if

Void Fraction:

EV

C V Vg

sg

m tT

1 C1 10 .

Pressure Drop: dP

dz

f V E

g Df

m m m g

c

2 12

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4.3.4. Annular Flow:

Transition Criteria:

V

gsg

l g

g

31 2.

0.25

Void Fraction: E where, X is the Lockhart - Martinelli parameterg

1 0 8 0 378

X . .

Pressure Drop:

dP

dz

f Vg D

c c g

c

2 2

where, c

V EV

V EV

sg g sl l

sg sl

fE

c

g

g

0 0791 75 1

0 25.Re

.

In all of the above equations,

m g l g gE E 1

f

DVm

m m

l from

4.3.5. Shear Stress Calculation

Once the pressure drop in the system is calculated, the shear stress (W ) exerted on the wall can be

calculated using the relation,

W

P

L

D

4

4.4 HORIZONTAL FLOW

The flow patterns in horizontal flow can be broadly divided into – stratified, wavy, annular, slug, bubble

and dispersed/mist flow- Figure 4.2 depicts the flow patterns pictorially. PREDICT 6.0 uses the flow map,

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Figure 4.3, proposed by Mandhane et. al.54

, based on 5935 flow pattern observations with an accuracy of

68.3%, to make an estimate of the flow pattern prevalent in the vertical system.

FIGURE 4.2 FLOW PATTERNS IN HORIZONTAL FLOW

Stratified flow occurs when the liquid flows along the bottom of the pipe and the gas flows over a

smooth liquid-gas interface. Wave flow occurs when the gas phase traveling at a greater velocity than the

liquid phase as to cause ripples in the liquid.

Annular flow occurs when the liquid forms a film around the inside wall of the pipe and the gas flows at

high velocities in the center of the pipe. Slug flow occurs when waves of liquid are picked up by a more

rapidly moving gas to form a frothy slug, which passes through the pipe at a much greater velocity than

the average liquid velocity. The gas phase is more pronounced than in bubble flow. Although the

liquid phase is still continuous the gas bubbles coalesce to form stable bubbles with almost the diameter

of the pipe. Slugs of liquid separate these large bubbles. The velocity of the bubbles is greater than that

of the liquid and can be predicted in relation to the liquid velocity. The liquid surrounding the gas

bubble travels at different velocities compared to the rest of the liquid phase. These variations result in

varying wall friction losses and also in liquid holdup. Both the gas and liquid phases have significant

effects on the pressure gradient.

Bubble flow occurs when bubbles of gas move along the upper part of the pipe at approximately the

same velocity as the liquid. Here, the gas is present as small bubbles randomly distributed, and their

diameters also vary randomly. The bubbles move at random velocities depending on their respective

diameter. Mist flow is the regime in which most or nearly all of the liquid is entrained as spray by the

gas. This is also called as dispersed flow/spray flow and may result in droplet impingement on the metal

surface, causing significant erosion damage. Here, the gas phase is continuous and the bulk of the liquid

is entrained in the gas.

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FIGURE 4.3 FLOW-PATTERN MAP OF MANDHANE ET. AL. FOR HORIZONTAL TWO-PHASE FLOW IN PIPES

4.4.1. Flow Pattern Prediction

The coordinates for transition boundaries between various flow regimes of proposed flow pattern map

are delineated in Table 1 where X and Y are the physical property correction factors,

XG L G

0 0808 62 4

72 4

0 018

0 2 0 25 0 2

. .

.

.

. . .

YL L

62 4

72 4

10

0 25 0 2

.

.

.

. .

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Transition Boundary VSG (ft/s) VSL (ft/s) Physical property correction - multiply

equation of transition boundary

by Stratified to elongated bubble 0.1

5.0 0.5 0.5

1.0/Y

Wave to slug 7.5 40.0

0.3 0.3

Y

Elongated bubble and slug to dispersed bubble

0.1 230.0

14.0 14.0

Y

Stratified and elongated bubble to wave and slug

35.0 14.0 10.5 2.5 2.5

3.25

0.01 0.1 0.2

1.15 4.8

14.0

X

Wave and slug to annular-mist 70.0 60.0 38.0 40.0 50.0

100.0 230.0

0.01 0.1 0.3

0.56 1.0 2.5

14.0

X

Dispersed bubble to annular-mist

230.0 269.0

14.0 30.0

X

TABLE 4.1: CO-ORDINATES FOR TRANSITION BOUNDARIES IN THE FLOW MAP

4.4.2. Liquid Hold-up Factor

Another important step in the prediction of pressure drop is the liquid hold-up factor. Liquid hold-up is

the actual portion of the tube occupied by the liquid. Beggs & Brill56

provide adequate relationships

among primary hydrodynamic variables for calculating the liquid hold-up, based on three broad flow

patterns:

1. Segregated flow - stratified, wavy, annular

2. Intermittent flow - plug, slug

3. Distributed flow - bubble, mist

The equations used for hold-up calculation are listed below:

For segregated flow:

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For intermittent flow:

For Distributed flow:

4.4.3. Pressure Drop Calculation

Calculating accurate pressure drop in tubing for a two-phase flow is not a simple task. A method

suggested by Duckler et. al.55

, has found good agreement in lab simulation. Relevant equations used for

pressure drop calculation are listed below:

Where,

NReTP is the two phase Reynolds No. used for the calculation of friction factor fo

() is the two-phase correction factor

GT is the total mass velocity

WT is the total mass flow rate

NS, G, L are no-slip, gas and liquid densities respectively

, HL are liquid fraction and liquid hold-up factor respectively

D is the diameter of the pipe

4.4.4. Shear Stress Calculation

Once the pressure drop in the system is calculated, the shear stress (w) exerted on the wall can be

calculated using the relation,

HN

L

FR

0 98 0 4846

0 0868

. .

.

HN

L

FR

0845 0 5351

0 0172

. .

.

HN

L

FR

1065 0 5825

0 0609

. .

.

w

P

L

D

4

P

L

G f

g D

T o

c NS

2 2

( )

NW

DTP

T

NS

Re 4

L

NS L

G

NS LH H

2 21

1

4.5 COMPRESSIBILITY FACTOR

PREDICT 6.0 includes the effect of compressibility of gases while calculating velocity and

pressure drop. The compressibility factor of natural gases is calculated using the Dranchuk

Abou-Kassem equations given below:

z AA

TA

TA

TA

T

AA

TA

TA

AT

AT

A AT

pr pr pr prpr

pr prpr

pr prpr

pr

pr

pr

A pr

1

1

12 3

34

45

5

67 8

22

97 8

25

10 11

2

2

311

2

where,

pr

pr

pr

P

zT

0 27. , is the pseudo reduced density

A1 through A11 are constants

Tpr is the pseudo reduced temperature

Ppr is the pseudo reduced pressure

4.6 INCLINED FLOW

Inclined flow is handled as per the correlations based on the publication by Beggs and Brill56

.

The approach to inclined flow modeling is of computing horizontal liquid hold-ups as mentioned

above and using a correction coefficient to account for the inclination.

The various types of flow regimes generated in horizontal flow, the inclination (whether flowing

uphill or downhill) and the input liquid content are the main parameters that affect this

coefficient.

Pressure drop is computed using the following equation:

pg

HH

dg

GfHH

g

g

dZ

dp

c

sgmLgLl

c

mmtp

LgLl

c

)]1([1

2)1(sin

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Where,

vm and vsg are the mixture and superficial gas velocities

L and G are the densities of the liquid and the gas phase

Gm is the mixture mass flux rate

d is the pipe diameter

ftp is the two phase friction factor

is the pipe inclination angle from horizontal

This total pressure drop takes into account the following three components:

1. Frictional Pressure Gradient

2. Acceleration Pressure Gradient

3. Gravity Pressure Gradient

This also accounts for the pressure recovery in downhill section of a pipeline and forms a part of

the flow model. An iterative procedure is implemented to perform a complete flow

characterization of the entire pipeline system to compute liquid holdup, pressure drop, shear

stress, superficial gas and liquid velocities for individual segments.

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5. CORROSION DISTRIBUTION PROFILE IN PREDICT 6.0

5.1 OVERVIEW

The problem of corrosion prediction across a pipeline or a tubing string is significant from a

stand point of the number of data points that need to be modeled and characterized. Given that

each corrosion prediction calculation in PREDICT 6.0 may require up to 50 input data parameters,

studying corrosion distribution across multiple points on a line immediately becomes a

substantial task.

In an effort to address the need to generate multi-point profiles across tubing strings or pipeline

segments, Honeywell has created a new corrosion distribution profile generation module in

PREDICT 6.0 that automates this onerous task. This chapter describes the extensive functionality

built into this module, and shows how the end user can, with minimal data specification, identify

and predict problem zones in a piping system and to analyze predicted corrosion rates and water

phase behavior at virtually any point along the pipe.

5.2 INTRODUCTION

One of the many crucial parameters for accurate corrosion prediction is the presence of liquid

water in the system. Water phase behavior is critical for two reasons:

Corrosion occurs only in the presence of a continuous conductive (aqueous) system

It is important to accurately characterize the liquid water in a system in order to assess the

water wettability with respect to other phases.

PREDICT 6.0 incorporates a rigorous model for accurate characterization of water phase behavior.

With correlations for water content of Natural Gas, corrections for sour gas, and vapor pressure

estimates for water at various conditions along a line, as well as information about total water to

gas ratio of the system, the condensation of water can be predicted. The Profile tool in PREDICT

6.0 takes into account the system water and evaluates the phase behavior, quantifies the

availability of liquid water and computes the corrosion rates along the pipeline. On the Process

Data tab, users provide gas composition, water analysis and inlet and outlet temperature and

pressure conditions. Once this is provided, users can select the Profile button under the Home

Menu to launch the Profile tool. The resulting profile screen is as shown below in Figure 5.1

As shown in the figure, users can perform the corrosion profile analysis on a series of segments

with different inclinations as well. Additional segments can be added by tabbing through the data

slots for each segment shown in the bottom panel. Users will be prompted to add another row of

data when the TAB key is clicked while in the last entry box for the row. Clicking Analyze will

refresh the screen with any changes made.

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Figure 5.1 – CORROSION PROFILE IN PREDICT 6.0

The temperature and pressure profiles are assumed to be linear along the pipe length and

corrosion rates are predicted at various points using the interpolated pressure, temperature, partial

pressures and the presence of water condensate at these conditions. These calculated corrosion

rates and water phase-behavior bars are plotted on the profile plot. The maximum allowed

corrosion rate is presented as a yellow line and for the piping to have a projected service life

greater than or equal to the desired (design) service life, the predicted corrosion rates should be

less than the permissible corrosion rate. In the example shown above the predicted corrosion

rates are greater than the permissible corrosion rate.

The profile plot can be copied by clicking on the copy button, this places the plot in the clipboard

and this can be pasted into any application such as MS-Word, MS-PowerPoint etc. Clicking on

Done will dismiss the Profile screen and show you the default consultation view.

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5.3 WATER PHASE BEHAVIOR COMPUTATIONAL BACKGROUND

PREDICT 6.0 uses the correlation of Bukacek and Maddox for computing the water content of

sour natural gas 62

. It utilizes Bukacek‘s correlation 61

for sweet gas, which is reported to be

accurate between 60 F and 460 F and for pressures from 15 to 10,000 psia. The factors for the

acid gas are accounted by Maddox Correlation 60

, which handles the contribution of CO2 and

H2S. These correlations for both H2S and CO2 are valid from 100 to 3000 psia. Temperature

ranges for their accuracy should be in the range of 80 F– 280 F for H2S and 80 F – 160 F for

CO2.

Bukacek’s correlation is given as:

BwPP

total

sat

water *47484

69449.66.459

87.3083log

tB

where w is in lb/MMSCF and t is in F. This is applicable only to sweet gas.

Maddox‘s method assumes that the water content of sour gas is the sum of three terms:

1. sweet gas contribution

2. CO2 contribution, and

3. H2S contribution.

The water content of the gas is calculated as a mole fraction weighted average of the three

contributions.

wywywy SHSHCOCOHCHCw

2222

Where,

w is the water content in lb/MMCF, y is the mole fraction and subscripts HC, CO2 and H2S for

hydrocarbon, hydrogen sulfide, and carbon dioxide respectively.

Carroll62

put forth a mathematical correlation by regressing the Maddox charts, to

programmatically compute water content w in lb/MMCF for H2S and CO2. This correlation is a

function of total pressure P in psia, and uses common logarithms.

2

210 )(logloglog PaPaaw

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The values for coefficients a0, a1 and a2 are reproduced in Table 6.0.

Temperature F (C)

a0 a1 a2

Carbon Dioxide

80 6.0901 -2.5396 0.3427 100 6.1870 -2.3779 0.3103 130 6.1925 -2.0280 0.2400 160 6.1850 -1.8492 0.2139

Hydrogen Sulfide 80 5.1847 -1.9772 0.3004

100 5.4896 -2.0210 0.3046 130 6.1694 -2.2342 0.3319 160 6.8834 -2.4731 0.3646 220 7.9773 -2.8597 0.4232 280 9.2783 -3.3723 0.4897

TABLE 5.1 Correlation Coefficients for Calculating the Maddox Correction for Water Content of

Sour Natural Gas, Carroll 62

To use this method, wHC is computed using a sweet gas method such as McKetta-Wehe chart,

(Bukacek is used in PREDICT 6.0) and the contributions for CO2 and H2S are computed from the

charts provided by Maddox, which were regressed and used for computing wCO2 and wH2S, this

also enables the correlations to be extrapolated beyond their suggested range to a certain extent.

Since the contribution by these gases is minor in most cases, the use of these extrapolations can

be justified. In cases with high H2S and CO2 content it is advisable to stay within the limits of the

Maddox correlation for an accurate water content estimate.

These equations and the system parameters are used to accurately estimate the phase behavior o

water in the system and predict the dew point temperature for water. The presence of liquid water

aggravates the corrosion problem and predicting its presence along a piping system is critical to

the accuracy to predicted corrosion rates.

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APPENDIX A: BIBLIOGRAPHY 1. C. S. Fang et al., ―Computer model of a gas condensate well containing carbon dioxide‖, Corrosion/89, Paper

465, New Orleans, NACE, 1989.

2. C. de Waard and U. Lotz, ―Prediction of CO2 corrosion of carbon steel‖, Corrosion/93, Paper 69, New

Orleans, 1993.

3. C. de Waard and D. E. Milliams., ―Carbonic acid corrosion of steel‖, Corrosion 31, 5, 1975, 177.

4. E. Dayalan et al., ―Modeling CO2 corrosion of carbon steels in pipe flow‖, Corrosion/95, Paper 118, Orlando,

FL, 1995.

5. J. D. Garber et al., ―Down hole parameters to predict mist flow and tubing life in gas condensate wells‖,

Corrosion/94, Paper 25, Baltimore, MD, 1994.

6. R. D. Kane and S. Srinivasan, Proceedings of CLI Workshop on oil and gas corrosivity, Abu Dhabi, April

1995.

7. L. H. Gatzky and R. H. Hausler ―A novel correlation of tubing corrosion rates and gas production rates‖,

Advances in CO2 Corrosion, Vol. 1, pp. 87, NACE 1984.

8. J. L Crolet and M Bonis., ―A tentative method for predicting the corrosivity of wells in new CO2 fields‖,

Advances in CO2 Corrosion, Vol. 2, pp. 23, NACE 1985.

9. A. Ikeda et al., ―Influence of environmental factors on corrosion in CO2 wells‖, Advances in CO2 Corrosion,

Vol. 2, pp. 1-22, NACE 1985.

10. C. D. Adams et al., ―Methods of prediction of tubing life for gas condensate wells containing CO2‖, 23rd

OTC,

Houston, TX, 1991.

11. Ketil Videm and Jon Kvarekval., ―Corrosion of carbon steel in CO2 saturated aqueous solutions containing

small amounts of H2S‖, Corrosion/94, Paper 12.

12. U. Lotz. et al., ―The effect of oil or gas condensate on carbonic acid corrosion‖, Corrosion/90, Paper 41.

13. H. J. Choi et al., ―Corrosion rate measurements of L-80 grade bottomhole tubular in flowing brines‖,

Corrosion/88, Paper 213, St. Louis, MO, 1988.

14. K. D. Efird, ―Predicting corrosion of steel in crude oil production‖, Materials Performance, Vol. 30, No. 3,

March 91, pp 63-66.

15. Arne Dugstad and Liv Lunde., ―Parametric study of CO2 corrosion of carbon steel‖, Corrosion/94, Paper 14.

16. U. Lotz., ―Velocity effects in flow-induced corrosion‖, Corrosion/90, Paper 27, Houston, Texas 1990.

17. Y. Gunatlun., ―Carbon dioxide corrosion in oil wells‖, Paper SPE 21330, SPE Middle East Oil Show,

Bahrain, 1991.

18. M. R. Bonis and J. L. Crolet., ―Basics of Prediction of risks of CO2 corrosion in oil and gas wells‖,

Corrosion/89, Paper 466, New Orleans, 1989.

19. R. H. Hausler and D. W. Stegmann ―CO2 corrosion and its prevention by chemical inhibition in oil and gas

production‖, Corrosion/88, Paper 363, St. Louis, MO, 1988.

20. R. D. Kane and S. Srinivasan ―Reliability assessment of Wet H2S Refinery and pipeline equipments: A

Knowledge-based systems approach‖, Serviceability of Petroleum, Process and Power Equipment, Eds. D.

Bagnoli, M. Prager and D. M. Schlader, PVP Vol. 239, ASME, NY, 1992

21. S. Srinivasan and R. D. Kane, ―Expert Systems for Selection of Materials in Sour Service‖, Proceedings of the

72nd

Annual GPA Convention, GPA, 1993, pp 88-92.

22. Linda G. S., et al., ―Effect of pH and temperature on the mechanism of carbon steel corrosion by aqueous

carbon dioxide‖, Corrosion/90, Paper 40, Las Vegas, 1990.

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23. Bonis M., and Crolet J. L., ―Practical aspects of the influence of in-situ pH on H2S induced cracking‖,

Corrosion Science, Vol. 27, No. 10/11, pp 1059-1070, 1987.

24. R. D. Kane et al., Internal Reports on multi-client program on safe use limits for steels, CLI International,

Inc., 1992-1994, Houston, Texas.

25. S. Srinivasan and R. D. Kane, ―Methodologies for reliability assessment of sour gas pipelines‖, Proceedings

of the Fifth International Conference on Pipeline Reliability, Gulf Publishing Co., Houston, Texas, Sept.

1995.

26. S. N. Smith and E. J. Wright, ―Prediction of minimum H2S levels required for slightly sour corrosion‖,

Corrosion/94, Paper 11, Baltimore, MD, 1994.

27. R. D. Kane, ―Roles of H2S in behavior of engineering alloys‖, International Metal Reviews, Vol. 30, No. 6,

1985, pp 291-302.

28. M. J. J. Simon Thomas and J. C. Loyless., ―CO2 corrosion in gas lifted oil production: Correlations of

predictions and field experience‖, Corrosion/93, Paper 79.

29. T. Murata et al., ―Evaluation of H2S containing environments from the view point of OCTG and line pipe for

sour gas applications‖, Paper No. OTC 3507, 11th

Annual OTC, 1979, Houston, Texas.

30. B. Lefebvre et al., ―Behavior of carbon steel and chromium steels in CO2 environments‖, Advances in CO2

Corrosion, Vol. 2, pp. 55-71, NACE 1985.

31. L.K. Sood et al., ―Design of surface facilities for Khuff gas‖, SPE Production engineering, July 1986, pp 303-

309.

32. K. D. Efird et al., ―Experimental correlation of steel corrosion in pipe flow with jet impingement and rotating

cylinder laboratory tests‖, Corrosion/93, Paper 81, New Orleans, 1993.

33. J. S. Smart III, ―A review of erosion corrosion in oil and gas production‖, Corrosion/90, Paper No. 10, 1990.

34. API 14-E, ―Recommended practice for design and installation of offshore production platform piping system‖,

III Edition, Dec. 1981, API, Dallas.

35. NACE Material Recommendation MR-01-75-94, NACE International, 1994.

36. K. D. Efird, Chapter on Petroleum Testing. In: Corrosion Tests and Standards - Application and

Interpretation, Ed: Robert Baboian, ASTM, June 1995, pp 350-358.

37. John S. Smart III, ―Wettability - A major factor in oil and gas system corrosion‖, Corrosion/93, Paper No. 70,

New Orleans, LA, 1993.

38. S. Olsen, ―Corrosion under dewing conditions‖, Corrosion/91, Paper 472, Cincinnati, 1991.

39. J. Oldfield and B. Todd ―Corrosion considerations in selecting metals for flash chambers‖, Desalination, 31,

1979, pp 365-383.

40. E. Dayalan et al., ―Influences of flow parameters on CO2 corrosion behavior of carbon steels‖, Corrosion/93,

Paper 72, New Orleans, 1993.

41. A. Dugstad et al., ―Influence of alloying elements upon the CO2 corrosion rate of low alloy carbon steels‖,

Corrosion/91, Paper 473, Cincinnati, 1991.

42. M. Kimura et al., ―Effects of alloying elements on corrosion resistance of high strength line pipe steel in wet

CO2 environment‖, Corrosion/94, Paper 18.

43. R. D. Kane et al., Multi-client proposal ―Prediction and Assessment of Corrosivity for Use of Steels in Multi-

phase CO2/H2S Environments‖, CLI International Inc., Oct. 1995.

44. Ciaraldi S. W., ―Materials failure in sour gas service‖, Corrosion/85, Paper 217.

45. Kane R. D., et al., ―Guidelines for selection of materials for H2S service‖, Battelle Summary Report, 1980.

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46. B. V. Johnson et al., ―Effects of liquid wall shear stress on CO2 corrosion of X-52 C-steel in simulated oilfield

production environments‖, Corrosion/93, Paper No. 573.

47. M. Kimura et al., ―Effects of alloying elements on corrosion resistance of high strength line pipe steel in wet

CO2 environment‖, Corrosion/94, Paper 18.

48. X. Zhou and W. P. Jepson., ―Corrosion in three phase oil/water/gas slug flow in horizontal pipes‖,

Corrosion/94, Paper 26.

49. C. A. Palacios and J. R. Shadley., ―CO2 corrosion of API N-80 steel in two-phase flow systems‖,

Corrosion/91, Paper 476.

50. Leigh Klein, ―H2S Cracking resistance of type 420 stainless steel tubulars‖, Corrosion/84, Paper 211.

51. M. B. Kermani et al., ―Experimental limits of sour service for tubular steels‖, Corrosion/91, Paper 21.

52. A. R. Hasan and Kabir., C. S., ―A Study of Multiphase Flow Behavior in Vertical Oil Wells: Part I -

Theoretical Treatment,‖ SPE, Paper No. 15138, 1986.

53. J. L. Crolet and Bonis, M. R., ―pH Mesurement Under High Prssures of CO2 and H2S,‖ Materials

Performance, May 1984, pp 35-42.

54. J. M. Mandhane et al., ―A Flow Pattern Map for Gas-Liquid Flow in Horizontal Pipes,‖ J. Multiphase Flow,

1974, Vol. 1, pp. 537-553.

55. A. E. Duckler et al., ―Frictional Pressure Drop in Two-Phase Flow B. An Approach Through Similarity

Analysis,‖ AIChE J., January 1964, pp. 44-51.

56. H. D. Beggs and Brill, J. P., ―A Study of Two-Phase Flow in Inclined Pipes,‖ JPT, May 1973, pp. 607-617.

57. Tomson, M. B., and Oddo, J. E., ―A New Saturation Index Equation to Predict Calcite Formation in Gas and

Oil Production,‖ Soc. Of Pet. Eng. Paper No. 22056, 1991.

58. Ionization Constants of inorganic acids and bases in aqueous solutions, compiled by D. D. Perrin, Pergamon

Press, Oxfordshire, 1964.

59. Stability Constants of metal ion complexes: Part A – Inorganic Liquids, compiled by Erik Hogfeldt,

Pergamon Press, Oxfordshire, 1982.

60. Maddox, R. N., Gas and Liquid Sweetening, 2nd

ed., John M. Campbell., pp.39-42, (1974) and Maddox, R.N.,

L.L. Lilly, M. Moshfeghian, and E. Elizondo, ―Estimating Water Content of Sour Natural Gas Mixtues‖,

Laurance Reid Gas Conditioning Conference, Norman, OK, Mar. (1988)

61. Bukacek – quoted in McCain, W.D., The Properties of Petroleum Fluids. 2nd

ed., PennWell Books, Tulsa,

OK, (1990)

62. John J. Carroll, The Water Content of Acid Gas and Sour Gas from 100 F to 220 F and Pressures to 10,000

psia, Gas Liquids Engineering Ltd., 81st Annual GPA Convention, Dallas, TX, (2002)

63. Donald D. Deford, “The Application of the Bronsted Concept to the Calculation of pH in Systems Involving

Two Acid-Base Couples”, Analytica Chimica Acta, 1951, pp. 352-356.

64. Jiabin Han, Yang Yang, Bruce Brown, Srdjan Nesic, “Electrochemical Investigation of Localized CO2

Corrosion on Mild Steel”, Corrosion/2007, Paper 323.

65. Anderko, N. Sridhar and D.S. Dunn, “A General Model for the Repassivation Potential as a Function of

Multiple Aqueous Solution Species”, Corrosion Science, 2004, pp. 1583-1612.

66. Anderko, N. Sridhar, D.S. Dunn and C. S. Brossia, “A Computational Approach to Predicting the

Occurrence of Localized Corrosion in Multicomponent Aqueous Solutions”, Corrosion/2004, Paper 61.

INDEX

A

Acetate .............................................................................. 42

acid number ...................................................................... 69

aeration ....................................................................... 44, 70

alloy ............................................................................ 44, 57

API-14E ............................................................................ 67

aqueous ............................................................................. 40

B

Benefits ............................................................................. 10

Bibliography ..................................................................... 95

bicarbonate ....................................................................... 58

bicarbonates ................................................................ 42, 64

Bockris .............................................................................. 58

Bonis ................................................................................. 60

buffer .......................................................................... 40, 42

C

Calculate

Friction Factor ............................................................. 22

Pressure Drop .............................................................. 22

Shear Stress ................................................................. 22

carbon dioxide .................................................................. 41

carbonic acid ..................................................................... 58

chlorides ..................................................................... 41, 64

Choi .................................................................................. 60

CLI Contact Information .................................................... 6

CO2

Effective partial pressure ............................................ 60

partial pressure of ........................................................ 60

CO2/H2S- corrosion .......................................................... 57

composition

temperature and ........................................................... 63

Compressibility ................................................................. 87

consult .............................................................................. 54

Conversions ...................................................................... 10

corrosion

allowance ..................................................................... 45

assessment ................................................................... 40

erosion ......................................................................... 57

local ............................................................................. 61

parameters ................................................................... 61

reaction ........................................................................ 58

corrosion allowance .......................................................... 45

corrosion rate

equation ....................................................................... 58

gas velocity .................................................................. 68

water content ............................................................... 70

cost analysis ...................................................................... 20

crude oil wettability .......................................................... 69

D

data entry .......................................................................... 19

Delta pH ........................................................................... 61

Density

Gas .............................................................................. 22

Oil 22

Water ........................................................................... 22

development ..................................................................... 56

dew point .......................................................................... 69

deWaard ..................................................................... 57, 58

Dialog

Flow Model ................................................................. 22

Ionic Strength ........................................................ 23, 24

Diameter ........................................................................... 22

Dugstad ............................................................................ 60

E

Electroneutrality equations ............................................... 61

English units ..................................................................... 10

environmental parameters ................................................ 40

erosion .............................................................................. 57

F

file

new .............................................................................. 50

open ............................................................................ 50

save ............................................................................. 51

Flow Modeling ................................................................. 22

Hoizontal..................................................................... 82

Vertical ....................................................................... 79

Flow Regime

Annular ..................................................... 79, 80, 82, 83

Bubble ............................................................. 79, 82, 83

Churn .......................................................................... 79

Mist ....................................................................... 82, 83

Slug ................................................................. 79, 82, 83

Stratified ............................................................... 82, 83

Wave ..................................................................... 82, 83

fluid velocity .................................................................... 44

Friction Factor .................................................................. 22

G

gas to oil ratio ................................................................... 43

gas velocity

corrosion rate .............................................................. 68

Gunatlun ........................................................................... 60

H

H2S

role of .......................................................................... 61

temperature and ........................................................... 64

heuristic ............................................................................ 56

horizontal flow ................................................................. 45

Horizontal Flow ............................................................... 82

FLOW MAP ................................................................... 84

FLOW PATTERNS .......................................................... 83

PREDICT®

6.0 User’s Guide

98


Liquid Hold-up ............................................................ 85

Pressure Drop .............................................................. 86

Shear Stress ................................................................. 86

Transition Boundaries ................................................. 85

hydrogen sulfide ............................................................... 40

I

Ikeda ..................................................................... 57, 59, 62

inhibition

batch ............................................................................ 46

continuous ............................................................. 46, 47

horizontal flow ............................................................ 46

method of ..................................................................... 46

no treatment ................................................................. 46

pigging ......................................................................... 46

squeeze ........................................................................ 46

vertical flow ................................................................. 46

Inhibition .......................................................................... 71

Efficiency ............................................ 71, 73, 74, 77, 78

inhibition efficiency .......................................................... 47

factors .......................................................................... 47

Install .............................................................................. 5, 6

interface ............................................................................ 50

Introduction ...................................................................... 56

Ionic Strength ................................................. 23, 24, 42, 43

K

kerogen ............................................................................. 69

L

life time cost ..................................................................... 21

literature ............................................................................ 57

Lotz ................................................................................... 60

M

mackinawite ...................................................................... 62

mechanical design ............................................................. 45

metallurgy ......................................................................... 57

Milliams ...................................................................... 57, 58

modeling parameters ......................................................... 57

multiphase ......................................................................... 66

Murata, T .......................................................................... 62

N

nomogram ......................................................................... 58

numerical .......................................................................... 56

O

oil phase ............................................................................ 69

Oldfield ............................................................................. 70

Overview............................................................................. 8

oxygen .............................................................................. 70

P

parameters ........................................................................ 61

superposition ............................................................... 57

persistence

oil phase ...................................................................... 69

pH

Bulk ...................................................................... 42, 61

delta ............................................................................ 61

Saturation .................................................................... 61

Saturation FeCO3 ........................................................ 42

Saturation FeS ............................................................. 42

pH 44

precipitation ..................................................................... 58

Predict

benefits ........................................................................ 10

consult ................................................................... 13, 54

consultation ................................................................. 15

Convert ....................................................................... 53

cost analysis .................................................... 20, 52, 53

description................................................................... 60

exit .............................................................................. 55

help ............................................................................. 52

install ............................................................................ 5

interface ...................................................................... 50

menus .......................................................................... 50

network ......................................................................... 6

results .......................................................................... 15

screen .............................................................. 12, 13, 14

setup .............................................................................. 5

single-user ..................................................................... 5

start up ............................................................ 12, 13, 14

technical support ........................................................... 6

toolbar ......................................................................... 50

using ............................................................................ 19

present worth .................................................................... 21

Production Rate

Gas .............................................................................. 22

Oil 22

Water ........................................................................... 22

pyrhotite ........................................................................... 62

R

ratio

gas/oil .......................................................................... 43

hydrocarbons/water ..................................................... 45

water/gas ..................................................................... 43

water/gas/oil ................................................................ 68

reactions ........................................................................... 58

reduction .......................................................................... 58

Roughness

Pipe ............................................................................. 22

S

Saturation

pH 61

Saturation pH

FeCO3 ......................................................................... 40

FeS .............................................................................. 40

PREDICT®

6.0 User’s Guide

99


service life ......................................................................... 45

setup .................................................................................... 5

Shear Stress....................................................................... 22

SI units .............................................................................. 10

sulfur ........................................................................... 44, 70

Synopsis ............................................................................ 56

System Requirements .......................................................... 5

T

Technical Description ....................................................... 56

Technical Support ............................................................... 6

temperature ....................................................................... 42

CO2 pressure ................................................................ 65

composition ................................................................. 63

H2S and ........................................................................ 64

oxygen concentration ................................................... 72

oxygen concentration ................................................... 73

velocity and ................................................................. 67

Temperature ...................................................................... 63

type of flow ....................................................................... 46

U

undissociated .................................................................... 58

units

english ......................................................................... 51

SI, metric ..................................................................... 51

Units

conversions .................................................................. 10

V

variables ........................................................................... 57

velocity ............................................................................. 65

temperature and ........................................................... 67

vertical flow ..................................................................... 45

Vertical Flow .............................................................. 79, 93

Annular Flow .............................................................. 82

Bubble Flow ................................................................ 80

Churn Flow ................................................................. 81

Patterns ....................................................................... 80

Pressure Drop .................................................. 80, 81, 82

Shear Stress ................................................................. 82

Slug Flow .................................................................... 81

Summary ..................................................................... 80

Void Fraction .................................................. 80, 81, 82

Videm ......................................................................... 59, 62

Viscosity

Gas .............................................................................. 22

Oil 22

Water ........................................................................... 22

W

water

condensed ................................................................... 64

formation ..................................................................... 64

water cut ..................................................................... 40, 69

water to gas ratio .............................................................. 43

wettability ......................................................................... 69

predict the corrosion rate

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