predict user manual

PREDICT 5.0

PROGRAM FOR EVALUATION AND DETERMINATION OF CORROSION

IN STEELS

USER’S GUIDE

PREDICT®5.0: User’s Guide

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 5.0 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 - 2009. All Rights Reserved.

Windows, Excel and Word are registered trademarks of Microsoft Corporation

2 Honeywell International, Inc.

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Table of Contents

USER’S GUIDE................................................................................................................................................................1 Table of Contents......................................................................................................................................................3

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

1.1 SYSTEM REQUIREMENTS FOR INSTALLING PREDICT 5.0...................................................................................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 5.0: DESCRIPTION AND UTILIZATION..................................................................................8

2.1 OVERVIEW – WHAT’S NEW IN PREDICT 5.0? ...................................................................................................8 2.1.1 PREDICT 5.0 Features and Benefits: Detail ...............................................................................................8 2.1.2 Benefits ..........................................................................................................................................................10 2.1.3 Units and Conversions...................................................................................................................................11

2.2 WORKING WITH PREDICT 5.0 .........................................................................................................................12 2.2.1 Important Pointers on Using PREDICT 5.0................................................................................................17 2.2.2 Cost Analysis in PREDICT 5.0....................................................................................................................18 2.2.3 Flow Modeling in PREDICT 5.0 .................................................................................................................19 2.2.4 Ionic Strength Calculation in PREDICT 5.0...............................................................................................21 2.2.5 Corrosion Distribution Profile Dialogs in PREDICT 5.0...........................................................................21 2.2.6 Multipoint Sensitivity Analysis in PREDICT 5.0.........................................................................................23 2.2.7 Access to JIP Corrosion Rate Data in PREDICT 5.0 .................................................................................24 2.2.8 Working with the PREDICT 5.0 Wizard ......................................................................................................27

2.3 ENVIRONMENTAL PARAMETERS IN CORROSION ASSESSMENT .......................................................................28 2.3.1 Hydrogen Sulfide (H2S) ............................................................................................................................29 2.3.2 Carbon Dioxide ........................................................................................................................................30 2.3.3 Chlorides ..................................................................................................................................................30 2.3.4 Bicarbonates.............................................................................................................................................30 2.3.5 Temperature .............................................................................................................................................31 2.3.6 Acetate and Ionic Strength .......................................................................................................................31 2.3.7 Gas to Oil Ratio........................................................................................................................................32 2.3.8 Water to Gas Ratio...................................................................................................................................32 2.3.9 Sulfur/Aeration .........................................................................................................................................32 2.3.10 Hydrogen ion Concentration (pH) ......................................................................................................33 2.3.11 Wall Shear Stress and Fluid Velocity ..................................................................................................33 2.3.12 Ratio of Hydrocarbons to Water .........................................................................................................34 2.3.13 Corrosion Allowance...........................................................................................................................34 2.3.14 Service Life ..........................................................................................................................................34 2.3.15 Type of Flow........................................................................................................................................34 2.3.16 Method of Inhibition ............................................................................................................................34 2.3.17 Inhibition Efficiency ............................................................................................................................35 2.3.18 Measured pH .......................................................................................................................................36

2.4 THE PREDICT 5.0 INTERFACE MENUS AND THE TOOLBAR .............................................................................36 2.5 GENERAL NOTES ON CONSULTING PREDICT 5.0 ............................................................................................39

3. TECHNICAL DESCRIPTION OF PREDICT 5.0 MODEL .......................................................................41

3.1 SYNOPSIS .......................................................................................................................................................41


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3.2 INTRODUCTION ..............................................................................................................................................41 3.3 CO2/H2S-BASED CORROSION: TECHNICAL BACKGROUND AND LITERATURE REVIEW...................................42 FE + 2H2CO3 ---> FE

++ + 2 HCO3

- + H2........................................................................................................................43

FE + 2HCO3- ---> FECO3+ H2O+CO2 ..........................................................................................................................43

3.4 PREDICT 5.0 MODEL DESCRIPTION ........................................................................................................................45 3.4.1 Role of H2S....................................................................................................................................................46 3.4.2 Temperature Effects.......................................................................................................................................48 3.4.3 Chlorides .......................................................................................................................................................49 3.4.4 Bicarbonates..................................................................................................................................................49 3.4.5 Wall Shear Stress and Liquid Velocity ..........................................................................................................50 3.4.6 Importance of Water/Gas/Oil ratios..............................................................................................................53 3.4.7 Oxygen/Sulfur ................................................................................................................................................55 3.4.8 Inhibition/Inhibition Effectiveness.................................................................................................................56 3.4.9 Incorporation of H2S Corrosion Data from JIP ............................................................................................58 3.4.10 Updated pH Prediction Model ....................................................................................................................59 3.4.11 Pitting Probability Model ............................................................................................................................61 3.4.12 Summary ......................................................................................................................................................63

4. FLOW MODELING IN PREDICT 5.0 .........................................................................................................64

4.1 OVERVIEW .....................................................................................................................................................64 4.2 INTRODUCTION ..............................................................................................................................................64 4.3 VERTICAL FLOW ............................................................................................................................................64

4.3.1. Bubbly Flow: .......................................................................................................................................65 4.3.2. Slug Flow: ...........................................................................................................................................66 4.3.3. Churn Flow: ........................................................................................................................................66 4.3.4. Annular Flow: .....................................................................................................................................67 4.3.5. Shear Stress Calculation ..........................................................................................................................67

4.4 HORIZONTAL FLOW .......................................................................................................................................67 4.4.1. Flow Pattern Prediction...........................................................................................................................69 4.4.2. Liquid Hold-up Factor .............................................................................................................................70 4.4.3. Pressure Drop Calculation ......................................................................................................................71 4.4.4. Shear Stress Calculation ..........................................................................................................................71

4.5 COMPRESSIBILITY FACTOR ............................................................................................................................72 4.6 INCLINED FLOW .............................................................................................................................................72

5. CORROSION DISTRIBUTION PROFILE IN PREDICT 5.0 ...................................................................74

5.1 OVERVIEW .....................................................................................................................................................74 5.2 INTRODUCTION ..............................................................................................................................................74 5.3 COMPUTATIONAL BACKGROUND ...................................................................................................................76

APPENDIX A: BIBLIOGRAPHY..........................................................................................................................78

INDEX........................................................................................................................................................................81


1. INSTALLATION

1.1 SYSTEM REQUIREMENTS FOR INSTALLING PREDICT 5.0

Requirements for using PREDICT 5.0 include:

• A Microsoft Windows compatible PC or workstation, with at least 512 MB (1 GB recommended) of RAM.

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

• Microsoft Windows XP or Microsoft Windows Vista (Vista Recommended)

• A CD-ROM drive for software installation

• Any platform that can support the Microsoft .NET Framework

• A hard disk with at least 100 MB of available file space

The PREDICT 5.0 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 5.0 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 5.0 installed on user machine to identify the license. Please do not connect the USB prior to software installation.

Insert the Installation Disk and go through the installation steps, 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 5.0 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.


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mailto:[email protected]


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 5.0 is supplied with a USB 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 5.0. The key will need to be attached to the computer any time you wish to use this software.

Double click on the PREDICT 5.0 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 5.0 or have problems installing or getting the program to execute properly, please contact support personnel at Honeywell International, Inc. for immediate assistance:

Honeywell International, Inc.

11201 Greens Crossing Blvd.

Suite 700, Houston, TX, 77067

(281) 444-2282 (Tel.)

(281) 444-0246 (Fax)

[email protected]

[email protected]

(b) If you have questions about the reasoning in PREDICT 5.0 or the decision-making rules or would like to have complete access to both the system development and technical expertise at Honeywell,


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you may procure annual maintenance and enroll in the PREDICT 5.0 Technical Support Program. The PREDICT 5.0 Technical Support Program provides several benefits, including:

Access to all the rules and decision-making mechanisms in PREDICT 5.0

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 5.0 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 5.0: DESCRIPTION AND UTILIZATION

2.1 OVERVIEW – WHAT’S NEW IN PREDICT 5.0?

PREDICT 5.0 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 5.0, 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 5.0 enhancements include:

A new, updated corrosion prediction model that incorporates data from the extensive Joint

Industry Project (JIP) on “Prediction and Assessment of Corrosion in Multiphase CO2/H2S environments”, conducted by Honeywell International, Inc, in a consortium consisting of major, global operating companies

New and 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 anion, cation species

A completely re-implemented and re-worked software interface, including the ability to automate analyses for multiphase production systems and flowlines

Support for current operating systems and software distribution frameworks (Windows® Vista and .Net)

2.1.1 PREDICT 5.0 Features and Benefits: Detail

PREDICT 5.0 represents the most significant upgrade undertaken by Honeywell for the PREDICT program series. The upgrade involved a complete 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 5.0 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 5.0 incorporate new data, analyses and field insights to give you the most accurate pH and corrosion prediction solution ever.


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PREDICT 5.0 enhancements may be partitioned into two groups:

1. Technology and model enhancements

2. User interface and automation enhancements

Technology and model enhancements include:

An enhanced corrosion prediction module which correlates corrosion in multiphase CO2/H2S systems to wall shear stress. This provides the program capabilities never before available in any prediction program for multiphase CO2/H2S applications (production / transmission)

Access to significant new JIP data on multiphase CO2/H2S corrosion behavior, integrated into the Predict 5.0 framework

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

An enhanced flow modeling module that provides key insights into understanding the contribution of typical flow-induced corrosion parameters, including the ability to analyze inclined uphill and downhill flows for shear stress and multiphase fluid dynamic characterization.

Ability to accurately model momentum transfer effects (flow regimes, void fractions, pressure drops and shear stresses) en-route to improved corrosion prediction

Ability to accurately determine scaling effects due to formation of Iron carbonate and Iron sulfide scales as a function of temperature and pH

A pitting probability indicator to characterize the likelihood of pitting corrosion and guide the end-user about modality of corrosion (pitting vs. general)

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.

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-Vista 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 A new PREDICT Consultation Wizard that collects relevant information through simple questions

and choices. Ability to share data with all Windows-compatible programs 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


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

Enhanced, Vista-compatible user friendly 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 delivery

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.

Cost analysis module facilitates comparison of project cost when using different materials or inhibitor options

Designed to effect significant reduction in time spent assessing corrosion Access to extensive consulting and development support from Honeywell in using/customizing

PREDICT 5.0


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2.1.3 Units and Conversions

PREDICT 5.0 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 5.0

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 5.0 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 5.0

2.2 WORKING WITH PREDICT 5.0

You can launch PREDICT 5.0 in one of two ways:

1. By double clicking on the PREDICT 5.0 icon on the Desktop

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

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, launch a wizard that will guide you to create a new consultation or access relevant online resources.


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FIGURE 2.2 – PREDICT 5.0 START UP SCREEN

Clicking on New 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 three tabs for Process Data, Flow Data and Project 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. 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. 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.

The lower part of the interface (Figure 2.3) shows the calculated results for predicted corrosion rate, pH, pitting probability, water phase behavior 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.


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FIGURE 2.3 – PREDICT 5.0 DEFAULT CONSULTATION

Based on the data specified for the different parameters, PREDICT 5.0 will instantaneously display the following results:

System Bulk pH

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.

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 5.0 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


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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 5.0 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 5.0.

The steps delineated below describe a typical PREDICT 5.0 consultation:

1. Specification of Process Data: To begin a PREDICT 5.0 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 5.0 is 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. GOR and WGR may be provided directly if needed by specifying these under Custom Fluid Properties on Flow Data tab. Also if Water Production Rate is not known, the saturated gas option can be selected on the Flow Data tab. Under saturated conditions the system will start condensing with any drop in temperature or increase in pressure.

2. Specification of Gas Composition: Gas composition for H2S and CO2 may be specified as either partial pressures or gas composition in mole %. 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. These data are used for the inlet conditions and the mole% values are used to compute the partial pressures at the outlet conditions. The results are automatically updated and refreshed.

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 5.0 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

5.0 to analyze if the corrosion allowance is sufficient to achieve the desired life based on the predicted corrosion rate.

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 5.0 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


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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

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 at Well Outlet: 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 5.0 handles ionic data for 16 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 5.0 has enhanced rules to assess corrosion damage due to oxygen in water (and acidic systems).

PREDICT 5.0 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 show 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 5.0. 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


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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

2.2.1 Important Pointers on Using PREDICT 5.0

As you go through a PREDICT 5.0 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 5.0 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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FIGURE 2.4 – PREDICT 5.0 TYPICAL CONSULTATION

2.2.2 Cost Analysis in PREDICT 5.0

PREDICT 5.0 facilitates 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:

Material costs (delivery, design, construction) data such as poundage and supply

Operating costs

Maintenance Costs

Taxes, Depreciation and salvage value

Recurring annual costs


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FIGURE 2.5 - COST ANALYSIS IN PREDICT 5.0

PREDICT 5.0 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 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 5.0 consultation. This ensures that all cost cases are at your fingertips while using PREDICT 5.0.

2.2.3 Flow Modeling in PREDICT 5.0

PREDICT 5.0 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


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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 be 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 5.0


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2.2.4 Ionic Strength Calculation in PREDICT 5.0

PREDICT 5.0 incorporates 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 automatically updates the ionic strength computed for the solution. In addition to these ions, PREDICT 5.0 evaluates 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.

FIGURE 2.7 – IONIC STRENGTH CALCULATION IN PREDICT 5.0

2.2.5 Corrosion Distribution Profile Dialogs in PREDICT 5.0

PREDICT 5.0 provides 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

ser 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

u


21


vertical flow, gas composition and water analysis at the wellhead is provided along with downhole 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.

FIGURE 2.8 - CORROSION DISTRIBUTION PROFILE IN PREDICT 5.0

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. The movement of the mouse over the plotted data points will display corrosion rates as well as the water phase distribution at a given point in the piping system. 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


22


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.

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

sion profile screen. For more details on corresponding input parameters on the lower part of corrogenerating a multi-segment corrosion profile please refer to Chapter 5 of this user’s guide.

2.2.6 Multipoint Sensitivity Analysis in PREDICT 5.0

PREDICT 5.0 provides 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

l effects of various parameters can be evaluated by choosing the X-axis he corrosion rate, pH, and system dew

of three small plots. Clicking on any of these plots shows the enlarged plot in

ted to be plotted on the X Axis are:

tion Rate

ction Rate

e

D

ates

Chlorides

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. Additionaparameter from the dropdown. The effect of that parameter on tpoint is shown in the formthe center of the screen.

Parameters that can be selec

Gas Production Rate

Water Produc

Oil Produ

Temperatur

Pressure

H S mol% 2

CO mol%2

Pipe or Tube I

Acetates

Bicarbon

Oxygen


23


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

Calculated Corrosion Rate

Calculated Dew Point

Calculated pH

FIGURE 2.9 – MULTIPOINT SENSITIVITY ANALYSIS – SELECTION OF PARAMETERS

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

2.2.7 Access to JIP Corrosion Rate Data in PREDICT 5.0

PREDICT 5.0 is the first program in the world of corrosion prediction model to provide users on-the-fly access to critical JIP data encompassing over 18 flow loop tests and 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 equilibria as a function of environmental and flow


24


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 own below in Figure 2.10, users may select an individual item and choose to view it as either an MS-

Excel file or an html file.

sh

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.

electrodes (FTE’s).

API 5L-X65, A106 Gr B, API 5L-X60 are the Pipeline materials used as laminar flow though electrodes (FTE’s).

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


25


A summary of the test conditions for all the 18 flow loop nte 2

Heat Treatment C

percent percent Grade/Supplier

s is prese d in Table .13

Steel Identifier arbon Cr Steel

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 st erca 0.5 Cr X65

eel 1 Hot Rolled >= 0.1 0.5 Sid

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

Steel Identifier Heat Treatment

percent percent Grade/Supplier Carbon Cr Steel

C-Mn steel 1 Quenched & Tempered

0.2 - 0.3 0.0 C-Mn L-80

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

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


26


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

2.2.8 Working with the PREDICT 5.0 Wizard

PREDICT 5.0 incorporates 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.


27


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 5.0 WIZARD

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

Temperature


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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 5.0 determines 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 temperature effect and predominates 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 5.0 can accurately predict corrosion rates for H2S partial pressure up to 500 psia.


29


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 5.0 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 ppm 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 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


30


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 5.0 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 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:

)ZM(5.0IS 2


31


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,

MW10xM

-3

Where,

x is concentration of each ion in ppm

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

2.3.7 Gas to Oil Ratio

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

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


32


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. 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. One measure which can be used to define the flow conditions is the superficial liquid velocity. 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. 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 downhole 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


33


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.

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:


34


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 downhole 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 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 downhole 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:


35


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 5.0 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

5.0, it is recommended that users utilize the highly accurate pH predictions from PREDICT 5.0.

2.4 THE PREDICT 5.0 INTERFACE MENUS AND THE TOOLBAR

PREDICT 5.0 is equipped with an intuitive graphical interface that facilitates easy access to the functionality of the program. The primary objective of the PREDICT 5.0 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


36


Figure 2.15 - PREDICT 5.0 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 5.0 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 5.0 Wizard will ask the user a series of questions to setup a consultation.

The Open command allows the user to open other stored consultations of PREDICT 5.0. The default extension for stored PREDICT 5.0 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.

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 MPS toolbar icon launches the Multipoint Sensitivity Analysis tool as described in Section 2.2.6


37


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 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 5.0 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 5.0 and in this manual.

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 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.

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 2.2.7

The Units Assistant icon allows the user to convert between British and Metric Units for most commonly used flow and operational parameters.

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 2.16

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 5.0.


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Figure 2.16 - PREDICT 5.0 Help Window

2.5 GENERAL NOTES ON CONSULTING PREDICT 5.0

PREDICT 5.0 has been completely re-designed to promote ease of use and compelling technical functionality. The best approach to learning the PREDICT 5.0 interface is to explore the program and its commands. The graphical interface is designed to be intuitive.

PREDICT 5.0 determines pH and corrosion rate through utilization of a complex numerical-heuristic model that incorporates data from extensive JIP data, literature, lab and field 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 5.0 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.


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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 5.0 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 5.0 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 5.0 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 5.0 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 5.0 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 5.0 system are the acid gases CO2 and H2S that contribute to the typically acidic pH found in production environments. The PREDICT 5.0 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

5.0 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 5.0 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 5.0 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 5.0 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 5.0 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 5.0 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 5.0 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 maximum corrosion rate even though it has been reported that the rate computed by the nomogram are


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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 5.0 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 damage.27

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 5.0 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 5.0 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


49


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 5.0 is given in Chapter 4.


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Effect of wall shear stress on corrosion rates, in PREDICT 5.0, 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 5.0 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 5.0 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/m3 (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 5.0 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.,


54


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/Mm3 (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. The PREDICT 5.0 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.


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Figure 3.10: Effect of oxygen concentration as a function of temperature on corrosion

3.4.9 Incorporation of H2S Corrosion Data from JIP

The PREDICT 5.0 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. - 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.


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- No effect of velocity was seen at low levels of H2S, indicating possible scaling of the coupons.

PREDICT 5.0 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 5.0 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

The ions in brackets are equilibrium concentrations and were computationally determined by following dissociation process.


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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 K1 H2S HS- + H+ K2 HS- S-2 + H+


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[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.

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.


61


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

]][[ 23

2

Where, [Fe2+] – Equilibrium concentration of ferrous ion in mol/l [CO3

2-] – 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 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.


62


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 5.0 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.


63


4. FLOW MODELING IN PREDICT 5.0

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 5.0 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 5.0 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.


64


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 Vsg sl t t tT 0 429 0 357. . or V

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 Vgsg

m t

0

CD

Dc

t0 12 0 371

. .

Pressure Drop: dP

dzf V

g Df

m m m

c 2 2


65


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 Vsg g l sl l sl

2 20 00673 50 .1.7

if V 2

Void Fraction: EV

C V Vgsg

m tT

1

CD

Dc

t1 12 0 90

. .

Pressure Drop: dP

dzf 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 Vsg g l sl l sl

2 20 00673 50 .1.7

if V 2

Void Fraction: EV

C V Vgsg

m tT

1 C1 10 .

Pressure Drop: dP

dzf V E

g Df

m m m g

c

2 12


66


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 EVsg g sl l

sg sl

f

Ec

g

g

0 0791 75 1

0 25.Re

.

In all of the above equations,

m g lE E 1 g g

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 5.0 uses the flow map,


67


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.


68



69

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

.

.

.

. .



70

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:

HN

LFR

0 98 0 4846

0 0868

. .

.

For intermittent flow:



71

HN

LFR

0845 0 5351

0 0172

. .

.

For Distributed flow:

HN

LFR

1065 0 5825

0 0609

. .

.

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:

P

L

G f

g D

T o

c NS

2 2

( )

Where,

NW

DTP

T

NSRe

4

L

NS L

G

NS LH H

2 21

1

ed for the calculation of friction factor fo NReTP is the two phase Reynolds No. us

ion factor ( ) is the two-phase correct GT is the total mass velocity

WT is the total mass flow rate NS, G, L are no-slip, gas and liquid densities respectively

iquid hold-up factor respectively , HL are liquid fraction and lD 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,

w

P

L

D 4

4.5 COMPRESSIBILITY FACTOR

PREDICT 5.0 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

prpr

pr

A pr

1

1

12 3

34

45

5

67 8

22

97 8

25

10 112

2

311

2

where,

prpr

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

HHdg

GfHH

g

g

dZ

dp

c

sgmLgLl

c

mmtpLgLl

c

)]1([1

2)1(sin


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.


73


5. CORROSION DISTRIBUTION PROFILE IN PREDICT 5.0

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 5.0 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 5.0 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 5.0 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

5.0 takes into account the system water and evaluates the phase behavior, predicts the presence 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.


74


Figure 5.1 – CORROSION PROFILE IN PREDICT 5.0

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.


75


5.3 COMPUTATIONAL BACKGROUND

PREDICT 5.0 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

t

B

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


76


The values for coefficients a0, a1 and a2 are reproduced in Table 5.1.

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 5.0) 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.


77


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 downhole 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.


79



80

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 31 acid number 54 aeration 32, 55 alloy 32, 42 API-14E 52 aqueous 29

B Benefits 10 Bibliography 78 bicarbonate 43 bicarbonates 30, 49 Bockris 43 Bonis 45 buffer 29, 30

C Calculate

Friction Factor 19 Pressure Drop 19 Shear Stress 19

carbon dioxide 30 carbonic acid 43 chlorides 30, 49 Choi 45 CLI Contact Information 6 CO2

Effective partial pressure 45 partial pressure of 45

CO2/H2S- corrosion 42 composition

temperature and 48 Compressibility 72 consult 39 Conversions 11 corrosion

allowance 34 assessment 28 erosion 42 local 46 parameters 46 reaction 43

corrosion allowance 34 corrosion rate

equation 43 gas velocity 53 water content 55

cost analysis 18 crude oil wettability 54

D data entry 17

Delta pH 46 Density

Gas 20 Oil 20 Water 20

development 41 dew point 54 deWaard 42, 43 Dialog

Flow Model 19 Ionic Strength 21

Diameter 19 Dugstad 45

E Electroneutrality equations 46 English units 11 environmental parameters 28 erosion 42

F file

new 37 open 37 save 37

Flow Modeling 19 Hoizontal 67 Vertical 64

Flow Regime Annular 64, 65, 67, 68 Bubble 64, 67, 68 Churn 64 Mist 67, 68 Slug 64, 67, 68 Stratified 67, 68 Wave 67, 68

fluid velocity 33 Friction Factor 19

G gas to oil ratio 32 gas velocity

corrosion rate 53 Gunatlun 45

H H2S

role of 46 temperature and 49

heuristic 41 horizontal flow 33 Horizontal Flow 67

FLOW MAP 69 FLOW PATTERNS 68


Liquid Hold-up 70 Pressure Drop 71 Shear Stress 71 Transition Boundaries 70

hydrogen sulfide 29

I Ikeda 42, 44, 47 inhibition

batch 35 continuous 35 horizontal flow 34 method of 34 no treatment 34, 35 pigging 35 squeeze 35 vertical flow 35

Inhibition 56 Efficiency 56, 58, 59, 61, 63

inhibition efficiency 35 factors 36

Install 5, 6 interface 36 Introduction 41 Ionic Strength 21, 31

K kerogen 54

L life time cost 19 literature 42 Lotz 45

M mackinawite 47 mechanical design 34 metallurgy 42 Milliams 42, 43 modeling parameters 42 multiphase 51 Murata, T 47

N nomogram 43 numerical 41

O oil phase 54 Oldfield 55 Overview 8 oxygen 55

P parameters 46

superposition 42 persistence

oil phase 54 pH

Bulk 31, 46 delta 46 Saturation 46 Saturation FeCO3 31 Saturation FeS 31

pH 33 precipitation 43 Predict

benefits 10 consult 12, 39 consultation 14 Convert 38 cost analysis 18, 38 description 45 exit 39 help 37 install 5 interface 36 menus 36 network 6 results 14 screen 12, 13, 14, 18 setup 5 single-user 5 start up 12, 13, 14, 18 technical support 6 toolbar 36 using 17

present worth 19 Production Rate


pyrhotite 47

R ratio

gas/oil 32 hydrocarbons/water 34 water/gas 32 water/gas/oil 53

reactions 43 reduction 43 Roughness

Pipe 19

S Saturation

pH 46 Saturation pH

FeCO3 29 FeS 29


82



83

service life 34 setup 5 Shear Stress 19 SI units 11 sulfur 32, 55 Synopsis 41 System Requirements 5

T Technical Description 41 Technical Support 6 temperature 31

CO2 pressure 50 composition 48 H2S and 49 oxygen concentration 57 oxygen concentration 58 velocity and 52

Temperature 48 type of flow 34

U undissociated 43 units

english 38 SI, metric 38

Units conversions 11

V variables 42 velocity 50

temperature and 52 vertical flow 33 Vertical Flow 64, 76

Annular Flow 67 Bubble Flow 65 Churn Flow 66 Patterns 65 Pressure Drop 65, 66, 67 Shear Stress 67 Slug Flow 66 Summary 65 Void Fraction 65, 66, 67

Videm 44, 47 Viscosity


W water

condensed 49 formation 49

water cut 29, 54 water to gas ratio 32 wettability 54

predict user manual

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