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Identifying Key Performance Indicators in Oilfield Water Handling Systems

Authors:
  • Infra-Tech Consulting LLC

Abstract and Figures

Key performance indicators are used to track the efficiency of the prevailing corrosion risk management strategy, namely, the integration of corrosion, process monitoring, inspection, mitigation, environmental control, and materials management. In an earlier paper1, a methodology was outlined for the use of a single key performance indicator, namely, the corrosion rate, in tracking monitoring strategy, mitigation strategy, and pipeline integrity. This paper seeks to identify other key performance indicators. At Kuwait Oil Company (KOC), internal corrosion monitoring activities are carried out in 22 gathering centers, early production facilities, 5 booster stations (operating), 3 effluent water disposal plants, seawater treatment plant, seawater injection plant, and pipeline network carrying different products. Corrosion and corrosivity trends are monitored using weight-loss coupons, electronic probes, bioprobes, hydrogen patch probes, galvanic probes as well as the measurement of iron content (total and dissolved) and manganese content. Corrosivity trend is also monitored using pH, conductivity, total dissolved solids, total hardness, dissolved oxygen, H2S concentrations, CO2 concentrations, bacterial population density and corrosion inhibitor residuals. These activities consume significant resources. The present paper is focused on identifying parameter(s) that could serve as key performance indicator(s) for corrosion and enable the company to operate with greater cost effectiveness, efficiency, reliability and control of the state of corrosion integrity of oilfield water handling systems. Key words: Key Performance Indicator (KPI), Corrosion Control Metrics, Corrosion trend, Corrosivity Trend, Corrosion Integrity.
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Identifying Key Performance Indicators for Corrosion in Oilfield Water Handling
Systems
Olagoke Olabisi, PhD
Director, Internal Corrosion Engineering
Corrpro Companies, Inc., Houston, Texas
oolabisi@corrpro.com
Amer Jarragh
Snr Corr Eng, Inspection & Corrosion Team
Kuwait Oil Company, Ahmadi, Kuwait
Yousef Khuraibut
Corr Engineer, Inspection & Corrosion Team
Kuwait Oil Company, Ahmadi, Kuwait
Ashok Mathew
Corrosion Chemist, KOC ICMS Contract
Corrpro Companies, Inc., Ahmadi, Kuwait
ABSTRACT
Key performance indicators are used to track the efficiency of the prevailing corrosion risk
management strategy, namely, the integration of corrosion, process monitoring, inspection,
mitigation, environmental control, and materials management. In an earlier paper1, a
methodology was outlined for the use of a single key performance indicator, namely, the
corrosion rate, in tracking monitoring strategy, mitigation strategy, and pipeline integrity. This
paper seeks to identify other key performance indicators. At Kuwait Oil Company (KOC),
internal corrosion monitoring activities are carried out in 22 gathering centers, early production
facilities, 5 booster stations (operating), 3 effluent water disposal plants, seawater treatment
plant, seawater injection plant, and pipeline network carrying different products. Corrosion and
corrosivity trends are monitored using weight-loss coupons, electronic probes, bioprobes,
hydrogen patch probes, galvanic probes as well as the measurement of iron content (total and
dissolved) and manganese content. Corrosivity trend is also monitored using pH, conductivity,
total dissolved solids, total hardness, dissolved oxygen, H2S concentrations, CO2
concentrations, bacterial population density and corrosion inhibitor residuals. These activities
consume significant resources. The present paper is focused on identifying parameter(s) that
could serve as key performance indicator(s) for corrosion and enable the company to operate
with greater cost effectiveness, efficiency, reliability and control of the state of corrosion
integrity of oilfield water handling systems.
Key words: Key Performance Indicator (KPI), Corrosion Control Metrics, Corrosion trend,
Corrosivity Trend, Corrosion Integrity.
1
Paper No.
4348
©2014 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, Publications Division, 1440 South Creek Drive, Houston, Texas 77084.
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.
INTRODUCTION
Kuwait Oil Company (1) is the sole exploration and producing Operator in Kuwait. Kuwait oil
reserve ranks 9th in the world and the Operator are projected to be producing about 4.0 million
barrels of oil per day by the year 2020. In the last 60 years of operation, the pipeline network
has grown to about 4,800 km. Corrpro (1) has been the Contractor for Internal Corrosion
Monitoring Services (ICMS) for the Operator since 2006. The ICMS Project conducts internal
corrosion monitoring of all existing facilities under the guidance of the Inspection and Corrosion
Team. For the Operator pipeline network, the Contractor conducts corrosion monitoring by
using:
1. Online weight-loss coupons for general/pitting corrosion, deposits, and sessile bacteria
2. Online electronic probes for general corrosion, deposits and sessile bacteria
3. Online bio-probes for sessile bacteria and deposits
4. Fluid sampling for planktonic bacteria analyses
5. Fluid sampling for chemical analyses and treatment chemical residual analyses
6. XRD analyses of solid corrosion products from shut-down vessels and suspended
solids from pig runs.
This paper relates to the activities of the ICMS contract pertaining specifically to oilfield water
handling systems. Generally, internal corrosion monitoring activities are carried out in 22
gathering centers, early production facilities, 5 booster stations (operating), 3 effluent water
disposal plants, seawater treatment plant, seawater injection plant, and pipeline network
carrying different products.
Inspection and monitoring are the two key processes by which the onset of internal corrosion,
external corrosion and stress corrosion cracking can be detected. However, internal corrosion
monitoring is able to detect corrosion significantly quicker than inspection techniques. This
“early detection” of the onset of corrosion enables a quick response to the changing
operational environment, and, when appropriate, an increase in the quantity of treatment
chemicals applied to the process fluids, thereby enhancing protection. Thus, internal corrosion
monitoring helps to minimize the extent of damage to the base materials, and maintain the
structural integrity of the production systems. That is, early detection assists risk-criticality
assessment, helps ensure reliability of production and enables the avoidance of losses from
equipment replacement and operational disruptions.
Online corrosion monitoring locations normally include: (a) each water source; (b) all points
downstream of storage units such as tanks; (c) downstream of all biocide injection points, (d)
plant outlets; (e) the farthest points in a system (e.g. injection wellhead); and (f) selected
worst-case locations (e.g. dead legs, etc.). Depending on risk assessment, fluid sampling is
conducted routinely at 30-day, 45-day, or 60-day intervals.
Weight-loss coupon corrosion monitoring is done typically at 45-day intervals for locations
exhibiting high (5 mpy equal to 0.127 mm/y) to severe (>10 mpy equal to >0.254 mm/y)
corrosion characteristics; 90-180 day intervals are used for locations with low (1 mpy equal to
0.0254 mm/y) to moderate (<5 mpy equal to <0.127 mm/y) corrosion characteristics and 6-
month intervals are used for locations with low corrosion (below 1 mpy equal to 0.0254 mm/y).
(1) Trade name
2
©2014 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, Publications Division, 1440 South Creek Drive, Houston, Texas 77084.
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.
Part of the corrosion monitoring activity involves analyses of corrosion products normally
recovered from the surfaces of weight-loss coupons. This includes XRD analysis of solid
samples, analysis of distilled water extracts using Hach spectrophotometer, conductivity meter,
and atomic absorption spectrometer as well as sessile bacteria growth analyses.
Following removal, coupons are cleaned using chemicals or glass-bead “blasting”. Weight
loss is measured for corrosion rates and pit depth is measured with a microscope for pitting
rates. The results are placed in a database and used for trending corrosion. Coupons are
photographed for later review and, as digital photographs, archived on database. The used
coupons are placed in treated envelopes and saved. Coupon corrosion rates are determined
using standard NACE RP0775-20052 while coupon processing methodology is per ASTM
procedure G1033. Bacteria growth analyses and interpretation are based on the Serial
Dilution Test Method outlined in NACE International Standard TM0194-20044.
In a recent paper5, a methodology was outlined for utilizing the effects of bacteria population
density on general/pitting corrosion to establish an asset integrity risk ranking for four oilfield
water handling systems. In that study, brackish water indicated a larger proportion of high and
severe general corrosion than the recycle, effluent water and seawater. This was correlated
with a similar larger proportion of brackish water samples showing SRB, GAB and GAnB
above the target levels. It was shown that the risk to each system is in the following decreasing
order: Brackish Water > Seawater > Recycle Water > Effluent Water.
The question then arises, is bacteria population the key performance indicator for corrosion in
oilfield water handling systems?
To answer that question necessitates the investigation of the effects of a variety of fluid
parameters on general and pitting corrosion. This paper is an attempt to do that; an attempt at
identifying the parameter(s) that could serve as key performance indicator(s) for corrosion in
oilfield water handling systems. To this end, corrosion and corrosivity trends are monitored
using weight-loss coupons, corrosion probes, bioprobes, hydrogen patch probes, galvanic
probes as well as the measurement of iron content (total and dissolved), and manganese
content. Corrosivity trend is also monitored using pH, conductivity, total dissolved solids, total
hardness, scaling ions (Ca & Mg), dissolved oxygen, H2S concentrations, CO2 concentrations,
carbonates, sulfates, sulfides, bacterial population density, oxygen scavenger residuals,
corrosion inhibitor residuals and scale inhibitor residuals.
CORROSION CONTROL METRICS FOR OILFIELD WATER HANDLING SYSTEMS
There are several generally accepted corrosion control matrices1 classified under system
measures, corrosion/erosion, fluid sampling/pigging, inspection, mitigation, repair and/or
replacements. In this study, however, the emphasis is on corrosion and corrosivity, discovered
through internal corrosion monitoring of the fluid parameters discussed in Table 1, entitled:
Significance of Fluid Parameters as Corrosion Control Metrics.
Each of the corresponding fluid parameters could be authentically considered a corrosion
control metric depending on its capacity to adequately reflect the corrosion state of the system.
Consider, for example, a system, which has been experiencing increased corrosion over a
period of time. If the trend of increasing corrosion rate versus time is relatable to the
3
©2014 by NACE International.
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NACE International, Publications Division, 1440 South Creek Drive, Houston, Texas 77084.
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.
corresponding plot of a parameter over that same period of time, it is perhaps probable that the
said parameter plays a role in the observed increased corrosion or corrosivity of the fluid.
Table 1
Significance of Fluid Parameters as Corrosion Control Metrics
S/N Parameter Significance
1 pH
pH of <7 indicates acidity of the fluid. A lower value of pH
indicates higher corrosivity.
2 Conductivity
A high conductivity of the fluid generally indicates high
corrosivity.
3 Chloride
Chloride acts as electrolyte in corrosion reactions. Corrosivity of
the fluid generally increases with an increased chloride content
4 Sulfate
Sulfate acts as electrolyte in corrosion reactions. Corrosivity of
the fluid generally increases with increased sulfate content.
However, sulfate contributes less to Corrosivity than Chloride.
5
Hydrogen
Sulphide (H2S)
H2S increases corrosivity of the fluid by providing H+ ions.
6 Total Hardness
As the hardness of the fluid increases, scaling tendency
increases. This may contribute to under-deposit corrosion.
7
Dissolved Oxygen
(DO)
High DO content indicates high corrosivity. Typically the DO
content is kept at <10 ppb by the use of oxygen scavengers.
8 Dissolved Iron
Dissolved iron content is a measure of corrosion. An increasing
trend of iron content might be indicative of increasing corrosion.
9 Total Iron
Total Iron indicates the sum of dissolved iron and insoluble iron
compounds. The difference between total and dissolved iron
indicates the amount of iron compounds formed due to
corrosion.
10 Manganese (Mn)
Mn is a major alloying element in carbon steel. A high Mn
content indicates high corrosion.
11
Corrosion Inhibitor
(C.I.) Residual
A higher content of C.I. Residual indicates decreased
corrosivity.
KEY PERFORMANCE INDICATORS (KPIs) FOR CORROSION
A key performance indicator (KPI) is a key corrosion control metric that can be used to
measure the efficiency of the prevailing corrosion risk management6 strategy, namely, the
integration of corrosion, process monitoring, inspection, mitigation, environmental control, and
materials management. KPI is a primary tool that can be used to proactively control corrosion
from growing to a size that could affect the structural integrity of components so that the
system remains sound and capable of safely performing the tasks for which it was designed
and is compliant with applicable regulations and standards governing design, operation, and
maintenance. KPI provides a reliable alert system against unexpected failures and leaks,
which could jeopardize mechanical integrity, operation, health, safety and environment (HSE).
To qualify as corrosion KPI, a corrosion control metric needs to be able to play a significant
role in focusing attention on the corrosion trends in the operating system. For oilfield water
handling systems, such parameter could be one or a combination of parameters, some of
4
©2014 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, Publications Division, 1440 South Creek Drive, Houston, Texas 77084.
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.
which appear in Table 1. Reliable data of such parameter(s) could enable decision-making and
the necessary planning for targeting the required corrosion mitigating measures. It could
therefore enable the organization to operate with greater efficiency, reliability and control of
production and avoidance of losses from equipment replacement and operational disruptions
FIELD DATA
In order to assess whether or not each parameter (or corrosion control metric) might indeed
qualify as a KPI, it is essential to compare the trend of each parameter to the corresponding
trends for general and pitting corrosion rates. The field data considered for this purpose are
collected from the year 2010 to 2013 based on coupon corrosion monitoring and fluid sampling
conducted at 45-day intervals. This applies to brackish, effluent, and recycle water systems.
The seawater system is not included in this study because its corrosion monitoring is
conducted at 6-month intervals during the period under consideration.
Presented below are the field data representing the trend of the parameters in Table 1. Each
parameter (with values for 2006-2013) appears on the ordinate to the left of each figure; values
for the corrosion/pitting rates appear on the ordinate to the right with the year from 2010 to
2013 on the abscissa. The plots are grouped according to the fluid type so that the
relationships can be easily discerned in a particular fluid. Figures 1 to 11 illustrate the trends of
the above mentioned parameters in effluent water system. Similar trends are found for the
brackish and recycle water systems, but are not shown below on account of space limitation.
The 2010-2013 data for all the three fluids (conducted at 45-day intervals) will, however, be
summarized below and utilized in the data analyses and interpretations.
GC-08 Effluent Water
0
2
4
6
8
10
Jan-06
Jan-07
Jan-08
Jan-09
Jan-10
Jan-11
Jan-12
Jan-13
Period
pH
0.1
1
10
100
1000
Corrosion Rate and
Ptting Rate (mpy)
Corrosion Rate (mpy) Pitting Rate (mpy) pH
Figure 1: Trend of pH and corrosion rates in Effluent Water System
(1 mpy = 0.0254 mm/y)
5
©2014 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, Publications Division, 1440 South Creek Drive, Houston, Texas 77084.
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.
GC-08 Effluent Water
0
100000
200000
300000
400000
500000
Jan-06
Jan-07
Jan-08
Jan-09
Jan-10
Jan-11
Jan-12
Jan-13
Jan-14
Period
Conductivity (us/cm)
0.1
1
10
100
1000
Corrosion Rate and
Ptting Rate (mpy)
Corrosion Rate (mpy) Pitting Rate (mpy) pH
Figure 2: Trend of Conductivity and corrosion rates in Effluent Water System
(1 mpy = 0.0254 mm/y)
GC-08 Effluent Water
0
20000
40000
60000
80000
100000
Jan-06
Jan-07
Jan-08
Jan-09
Jan-10
Jan-11
Jan-12
Jan-13
Jan-14
Period
Chloride (ppm)
0.1
1
10
100
1000
Corrosion Rate and
Ptting Rate (mpy)
Corrosion Rate (mpy) Pitting Rate (mpy) Chloride (ppm)
Figure 3: Trend of Chloride and corrosion rates in Effluent Water System
(1 mpy = 0.0254 mm/y)
6
©2014 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, Publications Division, 1440 South Creek Drive, Houston, Texas 77084.
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.
GC-08 Effluent Water
0
10
20
30
40
50
Jan-06
Jan-07
Jan-08
Jan-09
Jan-10
Jan-11
Jan-12
Jan-13
Jan-14
Period
Dissolved Oxygen (ppb)
0.1
1
10
100
1000
Corrosion Rate and Pitting
Rate (mpy)
Dissolved Oxygen (ppb) Corrosion Rate (mpy) Pitting Rate (mpy)
Figure 4: Trend of Dissolved Oxygen and corrosion rates in Effluent Water System
(1 mpy = 0.0254 mm/y)
GC-08 Effluent Water
0
2
4
6
8
Jan-06
Jan-07
Jan-08
Jan-09
Jan-10
Jan-11
Jan-12
Jan-13
Jan-14
Period
Hydrogen Sulphide (ppm)
0.1
1
10
100
1000
Corrosion Rate and
Ptting Rate (mpy)
Corrosion Rate (mpy) Pitting Rate (mpy) Hydrogen Sulphide (ppm)
Figure 5: Trend of Hydrogen Sulphide and corrosion rates in Effluent Water System
(1 mpy = 0.0254 mm/y)
7
©2014 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, Publications Division, 1440 South Creek Drive, Houston, Texas 77084.
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.
GC-08 Effluent Water
0
10000
20000
30000
40000
Jan-06
Jan-07
Jan-08
Jan-09
Jan-10
Jan-11
Jan-12
Jan-13
Jan-14
Period
Total Hardness (ppm)
0.1
1
10
100
1000
Corrosion Rate and
Ptting Rate (mpy)
Corrosion Rate (mpy) Pitting Rate (mpy) Total Hardness (ppm)
Figure 6: Trend of Total Hardness and corrosion rates in Effluent Water System
(1 mpy = 0.0254 mm/y)
GC-08 Effluent Water
0
2
4
6
8
Jan-06
Jan-07
Jan-08
Jan-09
Jan-10
Jan-11
Jan-12
Jan-13
Jan-14
Period
Dissolved Fe (ppm)
0.1
1
10
100
1000
Corrosion Rate and
Ptting Rate (mpy)
Corrosion Rate (mpy) Pitting Rate (mpy) Dissolved Fe (ppm)
Figure 7: Trend of Dissolved iron and corrosion rates in Effluent Water System
(1 mpy = 0.0254 mm/y)
8
©2014 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, Publications Division, 1440 South Creek Drive, Houston, Texas 77084.
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.
GC-08 Effluent Water
0
2
4
6
8
Jan-06
Jan-07
Jan-08
Jan-09
Jan-10
Jan-11
Jan-12
Jan-13
Jan-14
Period
Total Fe (ppm)
0.1
1
10
100
1000
Corrosion Rate and
Ptting Rate (mpy)
Corrosion Rate (mpy) Pitting Rate (mpy) Total Fe (ppm)
Figure 8: Trend of Total iron and corrosion rates in Effluent Water System
(1 mpy = 0.0254 mm/y)
GC-08 Effluent Water
0
1
2
3
4
5
Jan-06
Jan-07
Jan-08
Jan-09
Jan-10
Jan-11
Jan-12
Jan-13
Jan-14
Period
Manganese (ppm)
0.1
1
10
100
1000
Corrosion Rate and
Ptting Rate (mpy)
Corrosion Rate (mpy) Pitting Rate (mpy) Manganese (ppm)
Figure 9: Trend of Manganese and corrosion rates in Effluent Water System
(1 mpy = 0.0254 mm/y)
9
©2014 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, Publications Division, 1440 South Creek Drive, Houston, Texas 77084.
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.
GC-08 Effluent Water
0
10
20
30
40
Jan-06
Jan-07
Jan-08
Jan-09
Jan-10
Jan-11
Jan-12
Jan-13
Jan-14
Period
CI Residual (ppm)
0.1
1
10
100
1000
Corrosion Rate and
Ptting Rate (mpy)
Corrosion Rate (mpy) Pitting Rate (mpy) CI Residual (ppm)
Figure 10: Trend of Corrosion Inhibitor (CI) Residual Content and corrosion rates in Effluent
Water System (1 mpy = 0.0254 mm/y)
GC-08 Effluent Water
0
500
1000
1500
Jan-06
Jan-07
Jan-08
Jan-09
Jan-10
Jan-11
Jan-12
Jan-13
Jan-14
Period
Sulphate (ppm)
0.1
1
10
100
1000
Corrosion Rate and
Ptting Rate (mpy)
Corrosion Rate (mpy) Pitting Rate (mpy) Sulphate (ppm)
Figure 11: Trend of sulfates and corrosion rates in Effluent Water System (1 mpy = 0.0254
mm/y)
10
©2014 by NACE International.
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NACE International, Publications Division, 1440 South Creek Drive, Houston, Texas 77084.
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.
DATA ANALYSIS
All the figures indicate that general and pitting corrosion rates in effluent water system are
impacted somewhat by the fluid parameters. However, a distinct correlation is not discernable.
Similar results were obtained for brackish and recycle water systems. The summary of the
analytical results for the three different fluids appear in Table 2. Note that the table is
populated with the highest values for each parameter for each fluid, except for pH, which
represents the lowest value for each parameter for each fluid.
Table 2
Summary of Analytical Results of Different Fluid Streams
S/N Parameter
Values Obtained for Different Fluids
Brackish Water Recycle
Water
Effluent
Water
1 pH 6.2 6 5
2 Conductivity (µs/cm) 5800 15,000 320,000
3 Chloride (mg/L) 1250 6400 95,000
4 Dissolved Oxygen (DO)
(ppb) 10 5 20
5 Hydrogen Sulphide
(mg/L) 0.1 4.2 5
6 Total Hardness (mg/L) 2500 4000 35,000
7 Dissolved Iron (mg/L) 2 4.5 5
8 Total Iron (mg/L) 2 4.5 5
9 Manganese (mg/L) 0.5 0.5 2.5
10
Corrosion Inhibitor (C.I)
Residual (mg/L) 50 20 30
11 Sulphate (mg/L) 2200 1500 1000
Based on the above tabulated results, the corrosivity ranking of the water handling system is
essentially in the following decreasing order:
Effluent Water > Recycle Water > Brackish Water
How does the corrosivity ranking compare with the corrosion severity ranking for the same
11
©2014 by NACE International.
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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.
water handling system under the current production scenarios?
According to NACE RP0775-20052 corrosion severity classification is in terms of corrosion
rates in mils per year (1 mil = 0.001 in) or mm/y as illustrated in Table 3.
Table 3
Classification of General and Pitting Corrosion Rates
General Corrosion Pitting Corrosion
Low < 1.0 mpy (< 0.0254 mm/y) Low < 5.0 mpy (0.127 mm/y)
Moderate 1.0- 4.9 mpy
(0.0254-0.12446 mm/y)
Moderate 5.0 7.9 mpy
(0.127-0.20066 mm/y)
High 5 10 mpy
(0.127-0.254 mm/y)
High 8 15 mpy
(0.2032-0.381 mm/y)
Severe > 10 mpy (0.254 mm/y) Severe > 15 mpy (0.381 mm/y)
To interpret the weight-loss coupon data in terms of the corrosion severity classification given
in Table 3 as well as the corrosivity data depicted in Table 2, we resort to elementary statistics.
For each of the oilfield water handling systems, the incidents of ‘Severe’ general and pitting
corrosion during the period of 2010-2013 are presented in Table 4.
Table-4:
Summary of Corrosion and Pitting Rates of Different Fluid Streams
S/N Parameter
Incidents of severe corrosion (%)
Brackish Water
Recycle
Water
Effluent
Water
1
General corrosion Rate
(above 10 mpy)
67 20 9
2
Pitting Rate (above 15
mpy)
92 86 57
During the period, the locations prone to high and severe corrosion in these streams are
monitored on a 45-day interval. Based on these results, the corrosion severity ranking of the
water handling systems is in the following decreasing order:
Brackish Water > Recycle Water > Effluent Water
This is paradoxically the complete opposite of the corrosivity ranking. That is, there is no direct
correlation between the analytical results from fluid sampling vis-à-vis weight-loss corrosion
coupon results. This is a rather curious observation that might have been occasioned by the
presence of corrosion inhibitor residual in all the oilfield water handling systems. Although an
12
©2014 by NACE International.
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NACE International, Publications Division, 1440 South Creek Drive, Houston, Texas 77084.
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.
oilfield water-handling system might be corrosive, the continuous presence of a molecular
layer of corrosion inhibitor on the internal pipeline surface negates the effects of corrosivity.
Hence, bulk corrosivity of the oilfield water-handling system might be an inappropriate
performance indicator in the presence of effective corrosion inhibitor.
What then is responsible for the corrosion severity ranking noted above under the current
production scenarios?
It is perhaps occasioned by the order of susceptibility of the streams to Microbiologically
Influenced Corrosion (MIC). Indeed, in an earlier paper5 the effect of bacteria population
density on general and pitting corrosion was utilized to establish an asset integrity risk ranking
in the following decreasing order:
Brackish Water > Recycle Water > Effluent Water
This is exactly the same order observed above. Consequently, bacteria population density,
under the current production scenarios, is the key performance indicator. That is, effective and
efficient corrosion mitigation in a bacteria-infected MIC-susceptible water-handling system may
not be possible without an effective biocide even if corrosion inhibitor, oxygen scavenger and
other treatment chemicals are adequate. A judicious combination of treatment chemicals is
required for oil & gas companies to operate with greater cost effectiveness, efficiency,
reliability and control of the state of corrosion integrity of oilfield water handling systems.
Internal corrosion monitoring is therefore indispensable for pipeline integrity.
SUMMARY AND CONCLUSION
1 Internal Corrosion Monitoring is indispensable for pipeline integrity
2 Fluid chemistry is important for oilfield corrosivity trending.
3 Based on the fluid chemistry under the current production scenarios, the corrosivity
ranking of the oilfield water handling systems decreases in the following order:
Effluent Water > Recycle Water > Brackish Water.
4 The incidents of severe general corrosion observed in Brackish Water far exceed
those of Recycle and Effluent Water. The same is true for pitting corrosion.
5 The corrosion severity ranking of the oilfield water handling systems decreases in
the following order: Brackish Water > Recycle Water > Effluent Water.
6 Under the current production scenarios, Brackish Water is less saline and more
susceptible to microbial infestation and corrosion.
7 The paradoxical observation that Brackish Water is characterized by the lowest fluid
corrosivity and the highest corrosion severity could be ascribed to its MIC
susceptibility.
8 Corrosion inhibitor, in combination with other treatment chemicals without an
effective biocide, is ineffective in a bacteria-infected MIC-susceptible water-handling
system.
9 Bacteria population density is the key performance indicator in a bacteria-infected
MIC-susceptible water-handling system.
13
©2014 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, Publications Division, 1440 South Creek Drive, Houston, Texas 77084.
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.
REFERENCES
1. Olagoke Olabisi.Corrosion Rate as Key Performance Indicator in the North Slope”.
Material Performance, 52, 8 (2013)
2. Preparation, Installation, Analysis, and Interpretation of Corrosion Coupons in Oilfield
Operations, NACE International, NACE RP0775-2005.
3. ASTM G1 03, “Standard Practice for Preparing, Cleaning, and Evaluating Corrosion
Test Specimens,” American Society for Testing and Materials, PA, 2003
4. Field Monitoring of Bacteria Growth in Oil and Gas Systems, NACE International, NACE
TM0194-2004
5. A. R. Al-Shamari, A. W. Abdul Wahab Al-Mithin, Olagoke Olabisi, & Ashok Mathew.
Developing a Metric for Microbiologically Influenced Corrosion (MIC) in Oilfield Water
Handling Systems”. CORROSION/2013, Paper No. C2013-0002299, (Orlando, FL:
NACE 2013)
6. A. Morshed, “Improving Asset Corrosion Management Using KPIs”. Material
Performance. 47, 5 (2008)
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©2014 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, Publications Division, 1440 South Creek Drive, Houston, Texas 77084.
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.
... In this paper, an initial attempt is made to answer this question. The paper relates the findings of 16S rRNA characterization of bacteria to the activities of the ICMS program pertaining to microbiologically influenced corrosion (MIC) in oilfield water handling systems 5 According to NACE RP0775-2005 1 corrosion severity classification is in terms of corrosion rates in mils per year (1 mil = 0.001 in) or mm/y as illustrated in Table 1. On the other hand, certain morphology of corrosion pits is sometimes used to be a sign of MIC. ...
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One of the major challenges that face our national oil company is microbiologically influenced corrosion (MIC). In spite of biocide treatment in the facilities, the serial dilution results continue to confirm a high proliferation of sessile and planktonic bacteria in all the water handling systems. Planktonic and sessile samples from different gathering centers are now being analyzed for their molecular identities based on 16S rRNA characterization employing a molecular microbiological method (MMM) of quantitative polymerase chain reaction (qPCR) for enumeration of specific microorganisms. The results so far demonstrate the presence of ten principal groups of bacteria in brackish, effluent and sea water systems. These bacterial groups can be broadly classified as aerobic and anaerobic bacteria. This paper focuses on the linkage between the findings of 16S rRNA characterization with the field analyses of the diverse microbial population based on Serial Dilution Test Method outlined in NACE TM0194-2004. The key issues relate to the linkage of sulfate reducing bacteria, acid producing bacteria, general aerobic, and general anaerobic bacteria with specific microorganisms. The ultimate goal is the mitigation of MIC damage in the operating facilities by targeting specific microorganisms, identified by 16S rRNA, through a judicious selection of treatment chemicals.
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Managers as decision-makers present in different sectors should be supported in efficient and more and more sophisticated way. There are huge number of software tools developed for such users starting from simple registering data from business area – typical for operational level of management – up to intelligent techniques with delivering knowledge -for tactical and strategic levels of management. There is a big challenge for software developers to create intelligent management dashboards allowing to support different decisions. In more advanced solutions there is even an option for selection of intelligent techniques useful for managers in particular decision-making phase in order to deliver valid knowledge-base. Such a tool (called Intelligent Dashboard for SME Managers – InKOM) is prepared in the Business Intelligent framework of Teta products. The aim of the paper is to present solutions assumed for InKOM concerning on management of stored knowledge bases offering for business managers. The paper is managed as follows. After short introduction concerning research context the discussed supporting managers via information systems the InKOM platform is presented. In the crucial part of paper a process of knowledge transformation and validation is demonstrated. We'll focus on potential and real ways of knowledge-bases acquiring, storing and validation. It allows for formulation conclusions interesting from knowledge engineering point of view.
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Consider a crude oil handling system, with various degrees of water separation/accumulation, which has been experiencing increased corrosion over a period of time. If the trend of increasing corrosion rate versus time parallels the corresponding trend of water separation/accumulation as well as bacteria population density over that same period of time, the pragmatic assumption is to ascribe the source of increased corrosion not only to water separation/accumulation but also to the increased bacteria population density. This paper investigates the role of water separation/accumulation and bacteria population density on general/pitting corrosion and asset integrity in wet and dry crude handling systems. The study is intended to offer a viable corrosion control metric for microbiologically influenced corrosion (MIC) such that the population of sulfate reducing bacteria (SRB), general aerobic bacteria (GAB), and general anaerobic bacteria (GAnB) in an operating environment can be kept below a target envelop to preserve asset integrity.
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Bacteria population density may provide a viable corrosion control metric for microbiologically influenced corrosion (MIC) in oilfield water handling systems so that the population of the different strains of bacteria such as sulfate reducing bacteria (SRB), acid producing bacteria (APB) [also classified as general aerobic bacteria (GAB)] and general anaerobic bacteria (GAnB) in the operating environment can be kept below a target envelop. Consider, for example, a system that has been experiencing increased corrosion over a period of time. If the trend of increasing corrosion rate versus time parallels the corresponding plot of all bacteria population density over that same period of time, the general assumption is to ascribe the source of increased corrosion to increased bacteria population density. It is because of this empirical correlation that oil companies normally develop in-house guidelines for quantifying bacteria proliferation. There is, however, no generally accepted method for determining such guideline unambiguously. This paper provides a guidance to correlate the effects of bacteria population density on general and pitting corrosion rates with the goal of developing a self-consistent MIC performance indicator. It is based on microbiological and corrosion data obtained from various water handling systems at the Kuwait Oil Company. Key words: Microbiologically Influenced Corrosion, MIC, SRB, APB, GAB, GAnB
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Corrosion management is the systematic application of policies, practices, and resources to control corrosion and provide reliable safeguards against unexpected failures and leaks that can jeopardize mechanical integrity, operation, health, safety and environment. This paper highlights the use of a single key performance indicator in tracking monitoring strategy, mitigation strategy, and pipeline integrity for aboveground pipelines in the North Slope.
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Corrosion key performance indicators (KPIs) are valuable tools for monitoring the performance of an asset corrosion management strategy (CMS) that is crucial to mitigate the risk of corrosion in any oil and gas asset. Implementation of the asset CMS ensures that all the possible corrosion-related threats identified earlier are managed and mitigated so the integrity of the asset is maintained. KPIs are selected from the activities listed in a typical corrosion control matrices (CCM) document and then reported on a monthly basis in the form of percentage compliance. Corrosion KPIs are an effective way of capturing, trending, and assessing data related to the most important activities affecting the integrity of the process pressure systems of an asset. Use of corrosion KPIs as part of any asset CMS leads the several benefits such as improved personnel safety and environmental protection, reduced plant downtime, reduced cost of maintenance, inspection, and chemical treatment.
Standard Practice for Preparing, Cleaning, and Evaluating Corrosion Test Specimens
ASTM G1 – 03, " Standard Practice for Preparing, Cleaning, and Evaluating Corrosion Test Specimens, " American Society for Testing and Materials, PA, 2003
Installation, Analysis, and Interpretation of Corrosion Coupons in Oilfield Operations
Preparation, Installation, Analysis, and Interpretation of Corrosion Coupons in Oilfield Operations, NACE International, NACE RP0775-2005.