Real Time Corrosion Monitoring
Content
Paper No.
07268
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.
Copyright
©2007 by NACE International. Requests for permission to publish this manuscript in any form, in part or in whole must be in writing to NACE
International, Copyright Division, 1440 South creek Drive, Houston, Texas 777084. The material presented and the views expressed in this paper are
solely those of the author(s) and are not necessarily endorsed by the Association. Printed in the U.S.A.
1
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 offline 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
2
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 preweighed, 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
3
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:
4
1.
2.
3.
4.
5.
6.
7.
8.
Temperature
Pressure
Flow Rate
Chemical Injection Rate
Moisture Content
Valve Actuation (opening/closing)
Level Measurement,
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.
5
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
6
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:
7
•
•
•
•
•
•
•
•
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 debottlenecking 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.
8
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
9
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.
10
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.
.
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.
11
See periods of max. corrosion
Corrosion Rate
See only long term changes
Corrosion Rate
Metal Loss
See only cumulative damage
Date/Time
Date/Time
Off-line
Date/Time
Online
Weight Loss
Coupon
Off-line ER
Visual Inspection
UT inspection
Time
TimeFrame
Frame- -months
months
Mostly
Mostlymanual
manualtechniques:
techniques:
Time
Timeframe
frametoo
toolong
long
for
forprocess
processcorrelation;
correlation;
Good
Goodfor
forcumulative
cumulativedamage
damage
Online, Real-Time
Periodic UT
Super ER
On-line ER
Conventional LPR
SuperLPR technology
• multiple technique
electrochemical monitoring
(New data every 7 minutes)
Time
TimeFrame
Frame––days/weeks
days/weeks
Time
TimeFrame
Frame- -minutes
minutes
Time
Timeframe
framestill
stilltoo
toolong
long
for process correlation;
for process correlation;
Good for cumulative damage
Good for cumulative damage
Only
Onlytechnology
technologyconsistent
consistent
with
direct-to-DCS
with direct-to-DCSfor
forprocess
process
correlation
correlation&&optimization
optimization
Figure 3 – Schematic of migration of corrosion monitoring from offline to online.
Some offline techniques can also be migrated as automated assessment tools.
Asset Management
Solutions
Field Devices
Perimeter Monitoring/
Intrusion Detection
Energy Management
Solutions
Asset
Manufacturing Execution
Tracking
Systems (MES)
RFID
Training
Simulators
Safety
Shutdown
Systems
Mustering Solutions, Alarms, Egress
Water Management
Digital Video
Access Control
Human Machine Interface - Abnormal
Situation Manager
Corrosion Detection
and Monitoring
Advanced
Control
Gas Detection
Regulatory Control
Optimization
Fire Detection
Systems
CCTV Surveillance
Figure 4 – Measurements and functions possible in a modern industrial process control
and automation system.
12
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.
13
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.
14
A&C Server
TCP ÅÆ
Serial
Converter
Condition Monitoring
Wireless Infrastructure Network
Wi-Fi Clients
Wireless Devices
Figure 9 – Schematic representation of a wireless process control and automation environment.
Figure 10 – Pipeline SCADA System (schematic)
15
A
C
B
Figure 11 – Corrosion rates of carbon steel (A) and stainless steel (B)
viewed with neutralizer injection rate (C) in the plant DCS data historian.
16
07268
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.
Copyright
©2007 by NACE International. Requests for permission to publish this manuscript in any form, in part or in whole must be in writing to NACE
International, Copyright Division, 1440 South creek Drive, Houston, Texas 777084. The material presented and the views expressed in this paper are
solely those of the author(s) and are not necessarily endorsed by the Association. Printed in the U.S.A.
1
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 offline 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
2
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 preweighed, 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
3
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:
4
1.
2.
3.
4.
5.
6.
7.
8.
Temperature
Pressure
Flow Rate
Chemical Injection Rate
Moisture Content
Valve Actuation (opening/closing)
Level Measurement,
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.
5
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
6
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:
7
•
•
•
•
•
•
•
•
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 debottlenecking 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.
8
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
9
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.
10
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.
.
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.
11
See periods of max. corrosion
Corrosion Rate
See only long term changes
Corrosion Rate
Metal Loss
See only cumulative damage
Date/Time
Date/Time
Off-line
Date/Time
Online
Weight Loss
Coupon
Off-line ER
Visual Inspection
UT inspection
Time
TimeFrame
Frame- -months
months
Mostly
Mostlymanual
manualtechniques:
techniques:
Time
Timeframe
frametoo
toolong
long
for
forprocess
processcorrelation;
correlation;
Good
Goodfor
forcumulative
cumulativedamage
damage
Online, Real-Time
Periodic UT
Super ER
On-line ER
Conventional LPR
SuperLPR technology
• multiple technique
electrochemical monitoring
(New data every 7 minutes)
Time
TimeFrame
Frame––days/weeks
days/weeks
Time
TimeFrame
Frame- -minutes
minutes
Time
Timeframe
framestill
stilltoo
toolong
long
for process correlation;
for process correlation;
Good for cumulative damage
Good for cumulative damage
Only
Onlytechnology
technologyconsistent
consistent
with
direct-to-DCS
with direct-to-DCSfor
forprocess
process
correlation
correlation&&optimization
optimization
Figure 3 – Schematic of migration of corrosion monitoring from offline to online.
Some offline techniques can also be migrated as automated assessment tools.
Asset Management
Solutions
Field Devices
Perimeter Monitoring/
Intrusion Detection
Energy Management
Solutions
Asset
Manufacturing Execution
Tracking
Systems (MES)
RFID
Training
Simulators
Safety
Shutdown
Systems
Mustering Solutions, Alarms, Egress
Water Management
Digital Video
Access Control
Human Machine Interface - Abnormal
Situation Manager
Corrosion Detection
and Monitoring
Advanced
Control
Gas Detection
Regulatory Control
Optimization
Fire Detection
Systems
CCTV Surveillance
Figure 4 – Measurements and functions possible in a modern industrial process control
and automation system.
12
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.
13
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.
14
A&C Server
TCP ÅÆ
Serial
Converter
Condition Monitoring
Wireless Infrastructure Network
Wi-Fi Clients
Wireless Devices
Figure 9 – Schematic representation of a wireless process control and automation environment.
Figure 10 – Pipeline SCADA System (schematic)
15
A
C
B
Figure 11 – Corrosion rates of carbon steel (A) and stainless steel (B)
viewed with neutralizer injection rate (C) in the plant DCS data historian.
16
