IMPLEMENTATION OF REAL-TIME CORROSION MONITORING WITH INDUSTRIAL PROCESS CONTROL & AUTOMATION

by

R.D. Kane, D.C. Eden, S. Amidi and D. Delve Honeywell Process Solutions

14503 Bammel N. Houston Road, Suite 300 Houston, Texas 77014

ABSTRACT

Corrosion is a dynamic process, more so than even most corrosion engineers realize. It typically has a number of influencing factors that can vary with time and process variables, and so cause corrosion events or upsets to occur. The reason for the lack of appreciation of this situation is that historically long time intervals associated with inspections and off-line measurements do not afford the opportunity to correlate corrosion excursions with operating and process parameters This paper illustrates the importance of implementing an appropriate and correspondingly dynamic means of corrosion appraisal to help manage industrial processes and related corrosion prevention treatments, and to minimize corrosion upsets and failures, and maximize the availability of the plant assets. Value statements are provided that show the potential savings associated with online, real-time corrosion monitoring. Keywords: corrosion monitoring, process control, corrosion control, refining, pipeline, chemicals.

INTRODUCTION

In many regards, the job of the corrosion engineer has been classically an historical record-keeping process. That is to say, the tasks involving the measurement of corrosion damage have been documented over relatively long time intervals, typically months to years. This historical information is then used to confirm or predict:

• Effectiveness of corrosion control measures • Likelihood of future events (e.g. failures) • Need for maintenance functions.

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However, there have been many documented cases of disappointment where the historical trends were not predictive of future event and unforeseen situations have developed. For the most part, corrosion measurements have been accomplished with the exposure of corrosion (weight loss) coupons and off-line probes or with the help of inspection methods performed in a manual mode. Many times these approaches have been accompanied by corrosion problems that were not identified until after substantial corrosion damage or a failure occurred. There are new opportunities to improve the abovementioned situation and to elevate the corrosion engineer by providing a more critical and important function enabled through the implementation of online, real-time corrosion measurements. A further benefit is a substantial reduction in level of manual effort or the high expense currently required to support stand-alone corrosion management systems. Additionally, critical information is obtained sooner thus allowing correlation of corrosion events to process events. This new approach involves utilization of the existing data acquisition and automation systems that are already in place to handle industrial plant and production facilities. As an example, the Distributed Control System (DCS) is used to monitor and control processes, trend key process information, and manage and optimize system productivity in industrial plants. By integrating corrosion measurements into this system, corrosion monitoring can be easily implemented, automated and viewed with other process variables (PVs). This approach is more cost-effective than conventional, stand-alone systems, requires less manual labor to accomplish key tasks, and provides a greater degree of integration with systems in place to record, control and optimize. These systems can also more effectively distribute important information (corrosion and process data, related work instructions and follow-up reports) among different groups required for increased work efficiency and ease of documentation.

BACKGROUND Corrosion Rate: Perceived vs. Actual In field and plant operations, corrosion is typically viewed as the difference between two measurements performed over a rather long interval of time. These corrosion measurements commonly come from measured changes in metal thickness (e.g. from ultrasonic inspection readings made on components or electrical resistance changes made on probe elements) or mass loss readings (e.g. weight loss coupons) over a period of time, typically on the order of weeks, months or sometimes years. Two major shortcomings of this approach is that data indicates corrosion only after the damage has accumulated. Also, it only provides an average rate of metal loss during the measurement interval. Peak corrosion rates are not documented, and most importantly the specific time periods of peak corrosion rates, and the process conditions that produced, them are not identified. The abovementioned scenario has led to the generally held misconception that corrosion in industrial processes occurs at a relatively constant rate over time. In fact, a majority of the corrosion experiences in these processes actually occurs during short periods when specific process conditions develop. An example of this effect is shown in Figures 1 and 2. The data was obtained from a study conducted by the U.S. Department of Energy to identify “best practice” corrosion measurement techniques for monitoring pipelines.1-2 In this case, the pipeline environment was primarily oil (with varying water fraction, as may occur during normal production conditions). The pipeline was monitored with real-time corrosion measurements using electrochemical techniques and probes that were specifically selected for their compatibility with this type of “low-water” environment. These data were obtained with a totally remote

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and automated corrosion measurement system involving multiple electrochemical techniques, solar power and wireless data telemetry back to a pipeline control center. As presented in Figure 1, the data show that over a period of approximately two months, the corrosion rate was minimal for much of the time. However, there were approximately 20 episodes of high corrosion rate (corrosion upsets that were one to two orders of magnitude above baseline levels) during this period. Generally, the trend in corrosion rates increased with water content. However, as can be seen this was probably not the whole story and it was likely that these corrosion events were also coupled with another variable. In oil pipelines, periodically stratified flow conditions can develop at low flow rates where the brine separates from the oil leading to an increase in corrosion activity at the 6 o’clock position in the pipeline. In this case, the corrosion measurement was more sensitive than the infrequent process monitoring that was being performed. A similar situation was found for reportedly “dehydrated” gas pipeline systems that were susceptible to periodic dew point conditions. Figure 2 shows electrochemical monitoring data from a dehydrated hydrocarbon gas stream. During a two month period, six episodes of higher corrosion rate were observed. Whereas the magnitude of the corrosion excursions was not as great as in the oil/brine system, the excursions do constitute periodic and significant increases in the expected corrosion activity that will accumulate over time unless properly mitigated. The abovementioned cases highlight situations that could be remedied by better process control (hydration and/or flow control), or more effective dosing of inhibitors at intervals defined by the real-time corrosion measurement rather than based on historical average corrosion rates. A related condition in many gas pipeline systems is the need to maintain inlet pipeline gas quality to reduce out of specification conditions from moisture, CO2 or H2S. Understanding Terminology: Offline, Online, and Online, Real-time Corrosion coupons have been the “backbone” of industrial corrosion monitoring for over 50 years. They are simple to use, usually accurate, but completely manual. Therefore, coupon measurements are offline, labor intensive and not easily configured for automation and control systems. Coupons have to be pre-weighed, distributed to remote locations, installed, retrieved, examined, cleaned, re-weighed and the data processed. Therefore, a good deal of corrosion engineering and related technical staff time is taken up with manual and often routine tasks, also manipulating and viewing historically averaged, offline data. Alternatively, approaching corrosion assessment from an automation and control point of view would enable corrosion staff to focus on activities that have more value potential; a prime example is using their time to examine, interpret and understand critical underlying system attributes and relationships. Rather than spending time manually retrieving corrosion data, this information could be viewed on a local work station along with key process variables. In some cases, corrosion probes used to monitor industrial plants and pipelines are connected to field data loggers that are left to take corrosion rate measurements over a period of weeks or months. This approach is often referred to by corrosion engineers as “online monitoring” despite the fact that the data can not be accessed, viewed or acted upon in an online, real-time manner. These techniques can retrospectively identify peak corrosion rates and time periods. However, in these cases, corrosion probe data using conventional methods is typically considered qualitative, at best, due to limitations in the 1960’s measurement techniques used in most cases for field measurements. This information is viewed in isolation, without the PVs that allow its interpretation (i.e. PVs that relate to periods of corrosion upsets). Therefore, it is up to the corrosion engineer to try to locate and “piece together” the relevant process information and manually build correlations to understand the causes of corrosion upsets. In this case, the technical staff time often involves copious time to travel to remote locations to regularly

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retrieve corrosion data files and manually analyze logged data. Under these conditions, it is not surprising that the corrosion engineer is viewed as the bearer of “bad news” as the information is usually available only after the damage has occurred or, even worse, after critical failures have taken place. The perception of the current situation is that there is a high “per-point” cost associated with conventional corrosion monitoring approaches (largely due to the high cost of a separate infrastructure and large commitment of time and labor). Additionally, there is a low perceived value of what is basically historical data that are viewed weeks and month past due. Therefore, there is a tendency to limit resources for corrosion monitoring because this approach is expensive with only a limited chance of success. In many cases, problems are viewed after-the-fact and there is no way to a directly link cause and effect in a time frame that allows the damage to be cost-effectively prevented or minimized. Accordingly, corrosion measurement is relegated to mainly a confirmational reading of secondary importance rather than a primary variable that can be controlled and optimized with the process. The abovementioned situation is somewhat surprising. Many plant operators are trying to squeeze out one or two more percent improvement in efficiency and productivity. By comparison, corrosion costs are one of the few areas in plant operations where double digit improvements could be obtained in associated cost reduction particularly if lost production opportunity is included. In several cases in refineries (e.g. fractionator overhead and hydroprocessing) the cost of a single corrosion failure can be in the range of $35 million to $60 million.3 Even a few days of lost production can involve over $500,000 in lost production. Feedback of real-time corrosion rate data and adjusted chemical dosage has the benefit to offer additional gains in efficiency and reduced operating costs, also extended run time. Further confirmation of the potential cost saving based on the concept of providing “better corrosion information, sooner” and implementation of improved process control are apparent in the recent U.S. Cost of Corrosion Study4 and referenced in recent NACE technical committee reports.5 The cost of corrosion in the United States is around $300 billion or 4 percent of the gross domestic product, annually. Furthermore, estimates indicate that between 25 and 40 percent of this amount could be saved with better corrosion control efforts. Figure 3 shows a schematic representation of the migration of corrosion monitoring from a manual, offline process to an online, real-time process variable (PV). The initial driving force for this migration to online measurement is the benefit of automation; that is, reduced time and effort to obtain corrosion data with high data reliability. Then, corrosion as a PV takes on a new meaning when it can be viewed at a higher frequency (minutes) consistent with the way that other process variables are measured. More data brings increased statistical relevance, quicker response time, and a greater ability to understand corrosion in the context of the process being monitored. Therefore, the second driver for this migration is the ability to integrate the corrosion data immediately with other process data in an automated manner within the plant DCS system, rather than by the manual methods traditionally available to the corrosion engineer. A list of some of the usual PVs that are used and measured in industrial process control and automation systems are as follows:

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1. Temperature 2. Pressure 3. Flow Rate 4. Chemical Injection Rate 5. Moisture Content 6. Valve Actuation (opening/closing) 7. Level Measurement, 8. Analytical Data: ORP, pH, dissolved oxygen, etc.

Another consideration for integrating corrosion within the automation and control system is that the corrosion measurements need to be a ‘quantitative’ rather than a ‘qualitative’ indicator. This is because, now, this system will utilize the data to make assessments related to the management of the assets and the economic consequences of process changes and/or upsets. With this requirement also comes the concomitant need for accurate assessment of corrosion modality (e.g. general corrosion, pitting, local area attack, etc.). To date, there has not been a perfect method to assess all corrosion mechanisms. In most cases, except for certain forms of high temperature attack (e.g. naphthenic acid and sulfidic corrosion), corrosion involves electron transfer using an electrically conductive local or bulk environment. It has been shown that dew point conditions, many multiphase (oil/water) conditions with as little as 1-2 percent water, and even some fireside high temperature corrosion issues in fossil fueled boilers and waste incineration can be monitored using electrochemical methods.6-11 Therefore, if properly used, accurate corrosion measurements can be made in a matter of minutes using a suite of automated electrochemical techniques including Linear Polarization Resistance – LPR and Harmonic Distortion Analysis – HDA, and information obtained on the localized nature of corrosion using Electrochemical Noise – ECN. When coupled in an automated cycle, these techniques can provide two critical operator level corrosion PVs at a similar high frequency as that expected for other process variables:

• Corrosion Rate – LPR corrosion rate adjusted for a measured B value determine by HDA. • Pitting Factor – derived from ECN and LPR measurements, providing a three decade logarithmic

scale ranging from general corrosion, through a cautionary zone, to localized pitting corrosion. Two additional PVs can be also provided to the process control/automation system for specialist observation and involvement:

• B value – (also called Stern Geary constant) derived from HDA involving the real-time measurement of the anodic and cathodic Tafel slopes; used to adjust the LPR corrosion rates with the electrochemical processes in the system.

• Corrosion Mechanism Indicator (CMI) – indicating conditions and trends of passivity in stainless alloys, corrosion inhibition or scale formation.

In addition to these types of measurements, there may be a need to include other online-compatible measurements into the process control and automation system, when they can bring additional value or longer term corroboration for uses in asset assessment and integrity evaluation. The corrosion assessment techniques that fall into this group include those with the ability to be easily automated and be coupled with the modern communication methods such as wireless technologies. These include electrical resistance (ER) corrosion measurements, ultrasonic thickness (UT), pulsed eddy current (PEC), fiber optic (FO) strain measurement, as well as other ancillary techniques as may be necessary.

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Online, Real-Time Corrosion Implementation in a Plant Automation and Control Environment

In a modern industrial operation, the entire facility (whether centralized as in a refinery or chemical plant, or decentralized as in a pipeline network) is controlled by automation and control systems. These arrangements of process equipment, piping and pipelines are far too complex for operators to personally control every aspect of their operations. Therefore, they rely on a system of data acquisition and associated computer routines and applications to analyze the data and apply rule-based methodologies for assessing variations in process conditions and prioritizing the response. In modern industrial environments, these systems also provide management of safety and security. This is the infrastructure that has vastly improved the productivity of the modern industrial plant. In the 1970’s, when process automation and control technologies came to be employed, plants operated at about 70 percent daily productivity levels; with these newer technologies, productivity has progressed to over 90 percent, as shown in Figure 4. With current technology and initiatives such as abnormal situation management, the efforts are to both increase the number of operating days per year and increase productivity levels to over 95 percent. As shown by a 2004 survey, corrosion is by far the major factor accounting for petrochemical plant failures (Figure 5). The survey compared its results with those of a similar survey performed in 1984 and the situation appears unchanged over the past 20 years. Therefore, it is a foregone conclusion that corrosion needs to be integrated into automation and control strategies in industrial systems if this goal is to achieved. As mentioned previously, corrosion is one of the few remaining areas in many plant operations where double digit gains in cost savings can be made. An overview of the functions that are now being handled by industrial process control and automation systems is shown in Figure 6. Corrosion is just now entering this new environment. Once corrosion becomes a regularly used online, real-time PV it can be more fully integrated into this system. Then, the measurements can be more easily acquired and the data displayed with other key performance indicators (KPIs) in the plant data historian. Examples of integration of corrosion into the process control environment, where data are displayed in the system historian together with other KPI’s, are shown in Figures 7 and 8 for a key heat exchanger and a lean amine circuit, respectively. In Figure 7, the screen shows the major parameters that are normally used to monitor the health of a cooling water system. It can be seen that the electrochemical corrosion measurement captures a corrosion event where the LPR/HDA corrosion rates jump when the blow down occurs. Also shown, is that a large injection of corrosion inhibitor (as an automated process) decreased the corrosion rates until they are back down to normal levels. Figure 8 shows a similar configuration for the lean amine system reboiler circuit. An important aspect of the integration with the automation and control system is the seamless connectivity between varying job functions. Therefore, corrosion information becomes easily shared across a variety of job functions using a site or enterprise network. Corrosion control becomes part of everyone’s job function in a similar manner to quality control or safety, and the corrosion specialist can provide key real-time input to significant corrosion situations as they occur. Alerts can be automatically generated for specific job functions, such as inspection, maintenance, process control and engineering. Work orders and response reports related to corrosion can become automated functions, as well. Fault models can take the input corrosion data and apply rules to direct the fault indications to the most appropriate plant function - in a time frame where changes can avert major damage. A new technology making its way into plant automation and control environment is wireless. This is likely to be a major enabling technology for corrosion monitoring, as well. As shown in Figure 9, a

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wireless mesh of monitoring points can be created. This is particularly valuable for bring new information, such as corrosion, into the process control and automation system. The reason is that many of the locations where the new measurements will be required may not be presently hardwired. Based on experience obtained to date, the cost to install new home run wiring can be up to 10 times the price of the measurement device, thus making full implementation of new devices cost prohibitive. The development and use of automation technologies has also been extended outside of the normal industrial plant setting, as well. For example, pipeline systems are vast decentralized and remote transportation systems that have for years been monitored for corrosion using offline coupons over long intervals (30 to 90 days) and are inspected over still longer intervals (years) using manual ultrasonic testing and “smart-pigs” for general and localized wall loss. Online, real-time corrosion information had been considered too costly based on the need to set-up a separate data stream from remote locations. However, the current state of the art for automation and control for pipeline systems is the use of SCADA (Supervisory Control and Data Acquisition) systems. A schematic of a typical pipeline SCADA system is shown in Figure 10. SCADA technology was first utilized in the 1960’s and has evolved as the primary system for pipeline control and automation. The components of SCADA include a central computer for gathering and analyzing real time data along with remote terminal units (RTU) that are remote data collection devices and programmable logic controllers (PLC) or similar local control devices. At regular intervals, the SCADA system gathers operating conditions in the form of PVs (e.g., temperature, pressure, flow rate) or identification of locations where a leak on a pipeline has occurred and transfers the information back to the central computer on a real-time basis. The computer provides alerting of upset conditions and performs critical pipeline analysis and control functions using the remote data as input information in much the same way that DCS is used in more centralized plant applications. Besides using this system to monitor and control pipeline functions, it can also be utilized as an already installed data path to bring corrosion monitoring data back from remote pipeline locations. Instead of being limited to offline coupon data, data logged probe readings and inspection data on the monthly or longer basis, both process and corrosion engineers can access online, real-time corrosion data from remote pipeline sites. These monitoring points are located at critical locations identify by internal corrosion direct assessment (ICDA) software tools. This data can identify changes in operating conditions that result in high corrosion rates as shown in Figures 1 and 2. After the connectivity of corrosion data with other PVs is attained, existing programs (advanced process control applications) are available that can provide further assessment to identify key relationships between corrosion and other variables. Examples of functions handled in these applications are linear and non-linear modeling capabilities and data validation tools. These programs provide a means to positively identify single and multi-variant relationships between corrosion and other PVs. Early event detection is another functionality of the automation and control system, whereby correlations can be made among corrosion and other variables in a time domain that can identify the sequence of process events that lead up to corrosion upsets.

NEW VALUE PROPOSITIONS AND NEW INSIGHTS

Integration of corrosion with modern industrial process control technologies has been shown to bring substantial operational and cost savings opportunities for plant operators. The following are examples of value propositions obtained from discussions with refinery operations and corrosion personnel:

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• Increased ability to process crudes with higher margins – big savings and increased profits. • Cost of unscheduled shutdowns – as an example, a 400,000 bpd refinery may shut down for three

days to repair a corrosion leak. The cost at a $5 margin is $6,000,000. With better corrosion monitoring and operating variable evaluation, we can eliminate the cost of unscheduled shutdowns. Typically a refinery will have to run at a higher feed rate to make up the short fall.

• Improved asset reliability resulting in improved run length - 10% reduction in maintenance costs. • Improved desalter performance as a result of better corrosion monitoring – may result in a 2%

increase in crude feed rate, or potentially the ability to process 5% more of a poor quality crude. • Reduced HS&E exposure resulting from fewer unscheduled emissions to the environment – 3%

savings. • Improved safety record as a result of fewer shutdowns – 5% reduction in cost • Savings due to optimized chemical cost resulting from better monitoring – 10% • Increase operator effectiveness by bringing the corrosion data on line and in the control room.

Improved decision making with new insights and improved issue resolution time.

The benefits from the latter bullet item can be seen in a recent implementation of online, real-time in a hydrocarbon oxidation processing plant.11 This example involves monitoring performed at a plant where much of the equipment was constructed of carbon steel, 304L and 316L stainless steels. Decades of de-bottlenecking and other process modifications had produced corrosion problems. After a year of unsuccessful efforts to untangle their materials problems offline, an online, real-time electrochemical corrosion monitoring system was installed. Materials engineers, process engineers, and plant operators were then able to see immediate changes in corrosion behavior caused by specific variations in the process, enabling them to work together to identify process modifications and remedial actions to substantially reduce damage to equipment. Based on the results of the initial process evaluation that required only a few weeks, five predominant factors were confidently identified that related to the chemical aggressivity of the plant environment, which varied substantially with process and operational variables. These included:

• An upstream vessel was on an automatic pump-down schedule so that it pumped its contents into a reactor approximately once per hour. Every time the vessel pumped-down, the corrosiveness of the stream increased.

• Operators had varied the concentration of a neutralizing chemical in the process. However, contrary to expectations, it was found that increasing feed rate of a neutralizer increased corrosion rates rather than reducing them (Figure 10). This new information helped to both reduce corrosion rates and provide chemical engineers with new insight into the chemistry of the process.

• Following an initial evaluation of the corrosion data, a plant technician pointed out that an increase in corrosion rate of the 304L occurred right after they mixed a new batch of catalyst and it varied with feed rate which was controlled to minimize corrosive attack.

• The corrosion rate also varied quite significantly with process and operational events. These included noting that the corrosion rate of carbon steel correlated with the quantity of a key gaseous chemical used in the process.

• Short-term spikes to very high corrosion rates were observed week after week. The corrosion rate spikes coincided with the pumping of a laboratory waste stream into the process. Operators changed their procedure to dispose of lab samples another way, thus stopping the corrosion spikes.

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SUMMARY Corrosion behavior in process environments has a number of influencing factors that can vary with time and so cause dynamic corrosion events. The long intervals associated with inspections and off-line measurements do not afford the operator the opportunity to correlate corrosion excursions with operating and process parameters, making control a difficult proposition. This paper illustrates the importance of implementing an appropriate and correspondingly dynamic means of corrosion appraisal to help manage industrial processes and related corrosion prevention treatments, and to minimize corrosion upsets and failures, and maximize the availability of the plant assets.

REFERENCES

1. S. J. Bullard, B. S. Covino, Jr., G. R. Holcomb, J. H. Russell, S. D. Cramer and M. Ziomek-Moroz,

“Laboratory Evaluation of an Electrochemical Noise System for Detection of Localized and General Corrosion of Natural Gas Transmission Pipelines,” Paper # 03371, CORROSION/2003 (San Diego, CA, March 17-20, 2003), NACE International, Houston TX.

2. B. S. Covino, Jr., S. J. Bullard, S. D. Cramer, G. R. Holcomb, M. Ziomek-Moroz, M. S. Cayard, D. C.

Eden, and R. D. Kane “Evaluation Of The Use Of Electrochemical Noise Corrosion Sensors For Natural Gas Transmission Pipelines,” Paper No. 04157, Corrosion/2004 (New Orleans, LA, March 28-April 1, 2004), NACE International, Houston TX, 2004, 8 pp.

3. R. D. Kane, R.J. Horvath and M.S. Cayard, “Major Improvement in Reactor Effluent Air Cooler

Efficiency”, Hydrocarbon Processing, Sept. 2006, pp 99-111. 4. “Corrosion Costs and Preventive Strategies in the United States”, Supplement to Materials

Performance, NACE International, Houston, TX, July 2002, p. 3. 5. H. Alawalia, “Corrosion Technology Gaps Analysis”, Report Prepared for the NACE Technical and

Research Committee (TRAC) and Technical Coordinating Committee (TCC), Presentation at CTW/06, NACE International, Houston, TX, 2006.

6. R.D. Kane, D.A. Eden and D.C. Eden, “Online, Real-Time Corrosion Monitoring for Improving

Pipeline Integrity – Technology and Experience”, Corrosion 2003, Paper No. 03175, NACE International, March 2003.

7. R.D. Kane and E. Trillo, “Evaluation of Multiphase Environments for General and Localized

Corrosion”, Corrosion 2004, Paper No. 04656, NACE International, March 2003. 8. D.A. Eden and S. Srinivasan, "Real-time, On-line and On-board: The Use of Computers, Enabling

Corrosion Monitoring to Optimize Process Control", NACE Corrosion 2004, Paper #04059, NACE International, March 2004.

9. R.D. Kane and S. Campbell, “Real-Time Corrosion Monitoring of Steel Influenced by Microbial

Activity (SRB) in Simulated Seawater Injection Environments”, Corrosion 2004, Paper #04579, NACE International, March 2004

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10. B.S. Covino, Jr., S.J. Bullard, M. Ziomek-Moroz, G. R. Holcomb, D.A. Eden, “Fireside Corrosion Probes for Fossil Fuel Combustion”, Paper No. 06472, Corrosion 2006, NACE International, March 2006.

11. D.C. Eden and J.D. Kintz, "Real-time Corrosion Monitoring for Improved Process Control: A Real

and Timely Alternative to Upgrading of Materials of Construction", Paper #04238, Corrosion/2004, NACE International, Houston TX.

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Figure 1 – Real-time corrosion data on an oil pipeline. Two month interval – Corrosion Rate (B value corrected), Pitting Factor (σi/icorr) and water fraction.

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Figure 2 – Real-time corrosion data in a dehydrated hydrocarbon gas stream. The upper plot shows six episodes of corrosion over two months. The bottom plot highlights a shorter

interval to reveal the detail of a single upset likely related to upsets in dehydration.

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Figure 3 – Schematic of migration of corrosion monitoring from offline to online.

Some offline techniques can also be migrated as automated assessment tools.

Figure 4 – Measurements and functions possible in a modern industrial process control

and automation system.

Field Devices

Asset Management Solutions

Manufacturing Execution Systems (MES)

Regulatory Control

Safety Shutdown Systems

Training Simulators

Human Machine Interface - Abnormal Situation Manager

AdvancedControl

Optimization

CCTV Surveillance

Perimeter Monitoring/Intrusion Detection

Access Control

Asset Tracking RFID

Gas Detection

Energy Management Solutions

Fire Detection Systems

Mustering Solutions, Alarms, Egress

Digital Video

Corrosion Detection and Monitoring

Water ManagementField Devices

Asset Management Solutions

Manufacturing Execution Systems (MES)

Regulatory Control

Safety Shutdown Systems

Training Simulators

Human Machine Interface - Abnormal Situation Manager

AdvancedControl

Optimization

CCTV Surveillance

Perimeter Monitoring/Intrusion Detection

Access Control

Asset Tracking RFID

Gas Detection

Energy Management Solutions

Fire Detection Systems

Mustering Solutions, Alarms, Egress

Digital Video

Corrosion Detection and Monitoring

Water Management

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Off-line Online Online, Real-TimeSuperLPR technology• multiple techniqueelectrochemical monitoring(New data every 7 minutes)

Weight Loss Coupon

Off-line ER Visual Inspection UT inspection

Super ER

Conventional LPR

Periodic UT

On-line ER

See only cumulative damage See only long term changes See periods of max. corrosion

Time Frame - monthsMostly manual techniques:

Time frame too longfor process correlation;

Good for cumulative damage

Time Frame - monthsMostly manual techniques:

Time frame too longfor process correlation;

Good for cumulative damage

Time Frame – days/weeksTime frame still too longfor process correlation;

Good for cumulative damage

Time Frame – days/weeksTime frame still too longfor process correlation;

Good for cumulative damage

Time Frame - minutesOnly technology consistent

with direct-to-DCS for process correlation & optimization

Time Frame - minutesOnly technology consistent

with direct-to-DCS for process correlation & optimization

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Date/Time

Corr

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Off-line Online Online, Real-TimeSuperLPR technology• multiple techniqueelectrochemical monitoring(New data every 7 minutes)

Weight Loss Coupon

Off-line ER Visual Inspection UT inspection

Super ER

Conventional LPR

Periodic UT

On-line ER

See only cumulative damage See only long term changes See periods of max. corrosion

Time Frame - monthsMostly manual techniques:

Time frame too longfor process correlation;

Good for cumulative damage

Time Frame - monthsMostly manual techniques:

Time frame too longfor process correlation;

Good for cumulative damage

Time Frame – days/weeksTime frame still too longfor process correlation;

Good for cumulative damage

Time Frame – days/weeksTime frame still too longfor process correlation;

Good for cumulative damage

Time Frame - minutesOnly technology consistent

with direct-to-DCS for process correlation & optimization

Time Frame - minutesOnly technology consistent

with direct-to-DCS for process correlation & optimization

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Figure 5 – Schematic showing role of advanced process control functions and abnormal situation management (ASM)

Figure 6 – 2004 Survey of causes of failure in refining and petrochemical plants in Japan. A majority of the failures were due to corrosion.

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Figure 7 – Display of corrosion with other KPIs for a heat exchanger in the plant data historian.

Figure 8 - Display of corrosion with other KPIs for a lean amine reboiler line in the plant data historian.

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Figure 9 – Schematic representation of a wireless process control and automation environment.

Figure 10 – Pipeline SCADA System (schematic)

Wireless Infrastructure Network

Wi-Fi Clients

Condition MonitoringTCP

Serial Converter

A&C Server

Wireless Devices

Wireless Infrastructure NetworkWireless Infrastructure Network

Wi-Fi ClientsWi-Fi Clients

Condition MonitoringTCP

Serial Converter

A&C Server

Wireless DevicesWireless Devices

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Figure 11 – Corrosion rates of carbon steel (A) and stainless steel (B)

viewed with neutralizer injection rate (C) in the plant DCS data historian.

A

B

C

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