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The Role of Bacteria Population Density in Wet and Dry Crude Asset Integrity

Authors:
  • Infra-Tech Consulting LLC

Abstract and Figures

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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The Role of Bacteria Population Density in Wet and Dry Crude Asset Integrity
Dr. Olagoke Olabisi
Director, Internal Corrosion Engineering
Corrpro Companies, Inc., Ahmadi Kuwait
oolabisi@corrpro.com
Abdul Razzaq Al-Shamari
TL (S&E) Inspection & Corrosion Team
Saleh Al-Sulaiman
TL (N&W) Inspection & Corrosion
Amer Jarragh
Corr. Specialist. Inspection & Corrosion
Ashok Mathew
Corrosion Chemist, Inspection & Corrosion
Kuwait Oil Company, Ahmadi, Kuwait
ABSTRACT
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.
Key words: Bacteria Population Density, Sulfate Reducing Bacteria (SRB), General Aerobic
Bacteria (GAB), General Anaerobic Bacteria (GAnB), Microbiologically Influenced Corrosion
(MIC), Asset Integrity, Wet Crude, Dry Crude.
1
Paper No.
5534
©2015 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, 15835 Park Ten Place, 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 is the sole exploration and producing Operator in Kuwait. Kuwait oil reserve
ranks 9th in the world and the country is 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 has been the Contractor for Internal Corrosion Monitoring Services
(ICMS) since 2006. The ICMS contract is focused on conducting internal corrosion monitoring
of all existing facilities under the guidance of the Inspection and Corrosion Team. The Contractor
conducts corrosion and bacteria monitoring by using:
1. Mass-loss corrosion coupons for general/pitting corrosion, deposits, and sessile bacteria.
2. Electrical resistance (ER) and linear polarization resistance (LPR) probes for general
corrosion, deposits and sessile bacteria
3. Bio-probes for sessile bacteria and deposits.
4. Planktonic bacteria analyses of liquid samples from all facilities.
5. Fluid sampling for chemical analyses and treatment chemical residual analyses.
6. Chemical and bacteria analyses of deposits from pig runs.
7. XRD analyses of corrosion products from shut-down vessels and suspended solids.
This paper relates to the activities of the ICMS contract pertaining to microbiologically influenced
corrosion (MIC) in wet and dry crude handling systems. All facilities are equipped with on-line
corrosion and bacteria monitoring devices as indicated above. Online monitoring locations for
wet crude normally include: (a) Manifolds at the inlet of Gathering Centers (GCs); (b) Crude
Headers; (c) Gas Separators Inlet and Outlet; (d) Storage Tank; (e) De-salter Inlet and Outlet;
and (f) areas where the buildup of biofilms and hence, sessile bacteria growth are expected to
occur. Monitoring for dry crude includes “Dry Crude Export Line” but excludes “De-salter Inlet
and Outlet”, which does not exist within the dry crude handling system.
Depending on risk assessment, fluid sampling for chemical analyses and planktonic bacteria is
conducted routinely at 30-day, 45-day, 60-day or 90-day intervals. Mass-loss corrosion
monitoring is done typically at 45-day intervals for locations exhibiting high (5 mpy or 0.127
mm/y) to severe (>10 mpy or >0.254 mm/y) corrosion characteristics. The 90-180 day intervals
are used for locations with low (1 mpy or 0.0254 mm/y) to moderate (<5 mpy or <0.127 mm/y)
corrosion characteristics. Part of the corrosion monitoring activity involves testing for sessile
bacteria using deposits on mass-loss corrosion coupons. Samples of sessile bacteria are
normally recovered from the surface of corrosion coupons. Bacteria growth analyses and
interpretation for Sulfate Reducing Bacteria (SRB), General Aerobic Bacteria (GAB), and
General Anaerobic Bacteria (GAnB) are based on the Serial Dilution Test Method outlined in
NACE International Standard TM0194-20041. Mass-loss corrosion rates are determined using
standard NACE RP0775-20052 while coupon processing method is per ASTM procedure G1–
033. The data are grouped according to the fluid type so that the corrosion trends can be easily
discerned in a particular fluid.
In an earlier paper4, a methodology was outlined for the use of a single key performance indicator
in tracking monitoring strategy, mitigation strategy, and pipeline integrity for aboveground
pipelines in the North Slope. The present paper investigates the role of water
separation/accumulation and bacteria population density on general/pitting corrosion in
assessing asset integrity of wet and dry crude oil handling systems.
Trade name
2
©2015 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, 15835 Park Ten Place, 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.
APPROACH
Microbiologically influenced corrosion (MIC) is the degradation of a material under the influence
of environmental factors complicated by biotic activities. As its name implies, MIC involves
bacteria influencing corrosion. Frequently, the elements for a corrosion cell are present before the
bacteria become involved in the corrosion process. Conditions, which lead to microbial corrosion,
will often lead to corrosion, even if microbes were not involved. The presence and activity of
microorganisms greatly accelerates and/or concentrates the corrosion process. The biofilm,
consisting of the microorganisms involved in the corrosion process, are held in place by the matrix
of gelatinous extra-cellular polymeric substances (EPS), which is generally referred to as “slim”.
Corrosion is accentuated by the related activities of microorganisms and the build-up of metabolic
products in the slim has a significant influence on the nature and type of metal loss taking place.
The microbiological attack of process equipment used in the petroleum industry results in increased
operating expenses and reduced income. A partial list of these effects includes:
1. Cost of repair or replacement as well as clean up if/when a system fails.
2. Energy costs arising from line friction due to bacteria-induced build-up within
flowlines and pipelines.
3. Energy costs arising from reduced heat transfer due to bacteria-induced fouling.
4. Energy costs arising from injection well plugging induced by bacteria.
5. Clean-up costs associated with fouled and plugged injection wells, exchangers,
filters, and other assets.
6. Reduced income associated with product quality drop due to contamination
(produced products, products in storage, and refined products).
7. Cost of removing metabolic products such as sulfides, slime, etc.
8. Reduced income from downtime associated with any of the above.
9. Cost of mitigation, treatment chemicals, monitoring, and inspection programs.
Microbial corrosion activity occurs in wet and dry crude oil handling systems in addition to the
following water systems: seawater, brackish water, effluent water, recycle water, and firewater.
The microbial activity in crude oil systems is primarily due to the water separation and
accumulation taking place in crude headers, pipelines and storage tanks. To achieve effective
bacteria monitoring for these systems, monitoring devices are located in the areas where the
buildup of biofilms and hence, sessile bacteria growth are expected to occur. The monitoring
strategy facilitates, not only the identification of the prevailing bacteria, but also the
implementation of the required corrosion mitigating measures. In support of the ICMS program,
bacteria 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
microorganisms5. 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.
FIELD DATA
Sessile bacteria samples from wet and dry crude oil handling systems are recovered by the
monitoring crew from surfaces of corrosion coupons after retrieval. Following removal, coupons
are cleaned using chemical 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 corrosion trending. Coupons are photographed for later review and, as
digital photographs, archived in database. The used coupons are placed in treated envelopes
3
©2015 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, 15835 Park Ten Place, 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.
and saved. General corrosion rates (in mils per year) are calculated from the measured weight
loss as follows:
CR = [(weight loss in g)(22,300)/(area in inch2)(density in g/cm3) (365)/days of exposure] (1)
Pitting rates (in mils per year) are calculated from the maximum pit depth as follows:
Pitting rate = [(maximum pit depth in mils)(365)/days of exposure] (2)
Routine corrosion and sessile bacteria monitoring is conducted using strip corrosion coupons
for the wet and dry crude oil handling systems. The specific locations investigated for the present
study are presented in Table 1. The field data on bacteria, general and pitting corrosion are
taken from two representative gathering centers and utilized in the present investigation.
Table 1
Corrosion and sessile bacteria monitoring locations
Fluid Type Monitoring Locations
Wet Crude Manifolds at the inlet of Gathering Centers, Crude
Headers, Gas Separators Inlet and Outlet, Storage
Tank, De-salter Inlet and Outlet
Dry Crude Manifolds at the inlet of Gathering Centers, Crude
Headers, Gas Separators Inlet and Outlet, Storage
Tank, Dry Crude Export Line
CRUDE OIL SYSTEMS
Crude production wells are primarily classified as Wet Crude Wells and Dry Crude Wells. Wet
crude has a water-cut above 5% (v/v). Generally the water-cuts of wet crude wells vary within
the range of 5-30%(v/v). However, some locations in the facilities, classified as wet crude,
sometimes have less than 5 % (v/v) water cut. Also, some wet crude wells produce above 60%
water-cut. Crude oil is received in Gathering Centers (GC) through High Pressure (HP), Medium
Pressure (MP) or Low Pressure (LP) Headers.
Wet Crude Oil Handling System
Beyond the Wet Crude Headers, the crude separates to Gas and Liquid streams in a Gas
Separator, beyond which the wet crude goes into an Oily Water tank, where, owing to gravity,
oil and water separate into two layers. The oil layer is pumped to a De-salter for the removal of
salt water, which is piped to the Effluent Water tank. On-line corrosion monitoring devices are
installed in the locations discussed above. Sessile bacteria sampling and analyses are
conducted on deposits collected from corrosion coupons and probes. Inoculations of the
deposits in bacteria media are carried out in the field to minimize contamination and the demise
of the harvested bacteria in-transit. The wet crude samples are routinely collected and analyzed
for water-cut and various parameters to determine corrosivity. Such parameters include:
chlorides, sulfates, scaling ions (Ca, Mg), pH, conductivity and treatment chemical residuals.
The large volume of data collected makes it impractical to plot all the data points in what follows.
Nonetheless, plots are presented to illustrate the general data trends. Specific locations and
4
©2015 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, 15835 Park Ten Place, 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.
further descriptions of the results appear below under the section titled “BACTERIA
POPULATION DENSITY AS CORROSION CONTROL MATRIC”.
Figures 1 & 2 exemplify the trend of water cut, general and pitting corrosion rates in the wet
crude systems of Gathering Center number 3 (GC-03) and Gathering Center number 4 (GC-04),
respectively. Figures 3 & 4 exemplify the trend of bacteria population density, general and pitting
corrosion rates in the wet crude systems of GC-03 and GC-04, respectively. Note that some of
the data points are outside the plotted range; however, overall interpretations below will be based
on tabulated data. Note, also, that some wet-crude water-cut data points are below 5 % (v/v).
This is because some of the locations in the facilities, classified as wet crude, sometimes have
less than 5 % (v/v) water cut. This dichotomy appears to be smoothened out with time as will be
demonstrated below.
Figure 1: Trend of water cut, general and pitting corrosion rates in GC-03 wet crude
system (1 mpy = 0.0254 mm/y)
0
5
10
15
20
4/18/2006
3/17/2008
3/30/2010
1/10/2011
9/9/2011
10/23/2011
12/8/2011
4/14/2012
5/14/2012
10/8/2012
11/7/2012
3/9/2013
4/29/2013
10/19/2013
11/18/2013
Period
Corrosion Rate & Pitting Rate (mpy)
0
20
40
60
80
100
Water Cut %, v/v
Corrosion Rate Pitting Rate Wet Crude Water Cut
Figure 2: Trend of water cut, general and corrosion pitting rates in GC-04 wet crude
system (1 mpy = 0.0254 mm/y)
0
10
20
30
40
0
2
4
6
8
10
Water Cut %, v/v
Corrosion Rate & Pitting Rate (mpy)
Corrosion Rate Pitting Rate Wet Crude Water Cut
5
©2015 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, 15835 Park Ten Place, 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.
figure 3: Trend of bacteria population, general and pitting corrosion rates in GC-03
wet crude system (1 mpy = 0.0254 mm/y)
0
5
10
15
20
4/18/2006
3/17/2008
3/30/2010
1/10/2011
9/9/2011
10/23/2011
12/8/2011
4/14/2012
5/14/2012
10/8/2012
11/7/2012
3/9/2013
4/29/2013
10/19/2013
11/18/2013
Period
Corrosion Rate & Pitting Rate (mpy)
0.1
1
10
100
1000
10000
100000
Counts/cm2
Corrosion Rate mpy Pitting Rate (mpy) SRB GAB GAnB
Figure 4: Trend of bacteria population, general and pitting corrosion rates in GC-04
wet crude system (1 mpy = 0.0254 mm/y)
Note that the corrosion data presented in all figures are for the period of 2011-2013 whereas the
bacteria data cover the period of 2006-2013. Consequently, discussion about possible
correlation between bacterial population and corrosion data will relate only to the period of 2011-
2013. This will be demonstrated with tabulated data plus additional descriptions below under the
section titled “BACTERIA POPULATION DENSITY AS CORROSION CONTROL MATRIC”.
Dry Crude Oil Handling System.
Beyond the Dry Crude Headers, the crude separates to Gas and Liquid streams in a Gas
Separator, after which the crude goes into a Dry Crude Tank which serves as the Export Crude
Tank. On-line corrosion monitoring devices are installed in the locations discussed above.
0.1
1
10
100
1000
10000
100000
0
2
4
6
8
10
Counts/cm2
Corrosion Rate & Pitting Rate (mpy)
Corrosion Rate mpy Pitting Rate (mpy) SRB GAB GAnB
6
©2015 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, 15835 Park Ten Place, 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.
Following the same procedures as those for wet crude oil handling system, sessile bacteria,
water-cut and various other parameters were analyzed for the dry crude oil handling system.
Figures 5 & 6 exemplify the trend of water cut, general and pitting corrosion rates in the dry
crude systems of GC-03 and GC-04, respectively. Figures 7 & 8 exemplify the trend of bacteria
population density, general and pitting corrosion rates in the dry crude systems of GC-03 and
GC-04, respectively. As indicated above, some of the data points are outside the plotted range
and tabulated data will be used in data interpretation under the section titled “BACTERIA
POPULATION DENSITY AS CORROSION CONTROL MATRIC”.
Figure 5: Trend of water cut, general and pitting corrosion rates in GC-03 dry crude
system (1 mpy = 0.0254 mm/y)
Figure 6: Trend of water cut, general and pitting corrosion rates in GC-04 dry crude
system (1 mpy = 0.0254 mm/y)
0
2
4
6
8
10
0
2
4
6
8
10
Water Cut %, v/v
Corrosion Rate & Pitting Rate
(mpy)
Corrosion Rate Pitting Rate Dry Crude Water Cut
0
0.2
0.4
0.6
0.8
1
0
1
2
3
4
Water Cut %, v/v
Corrosion Rate & Pitting Rate (mpy)
Period
Corrosion Rate Pitting Rate Dry Crude Water Cut
7
©2015 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, 15835 Park Ten Place, 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.
Figure 7: Trend of bacteria population, general and pitting corrosion rates in GC-03
dry crude system (1 mpy = 0.0254 mm/y)
Figure 8: Trend of bacteria population, general and pitting corrosion rates in GC-04
dry crude system (1 mpy = 0.0254 mm/y)
It needs be repeated that the corrosion rates data presented in the above figures are for the
period of 2011-2013 whereas the bacteria data cover the period of 2006-2013. In what follows,
discussion about possible correlation between bacterial population density and corrosion rates
data will only relate to the period of 2011-2013.
DATA ANALYSIS
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 2. On the other hand, certain
morphology of corrosion pits is sometimes used to be a sign of MIC. For example, a terraced pit
0.1
1
10
100
1000
10000
0
2
4
6
8
10
Counts/cm2
Corrosion Rate & Pitting Rate (mpy)
Period
Corrosion Rate mpy Pitting Rate (mpy) SRB GAB GAnB
0.1
1
10
100
1000
10000
0
1
2
3
4
Counts/cm2
Corrosion Rate & Pitting Rate (mpy)
Period
Corrosion Rate mpy Pitting Rate (mpy) SRB GAB GAnB
8
©2015 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, 15835 Park Ten Place, 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.
is accepted as indicative of SRB but ‘pits within pits’ and/or tunneling is accepted as indicative
of APB/GAB. Because such morphologies could be elucidated in terms of abiotic mechanisms
as well, corroboration is normally sought for biotic mechanisms based on bacteria growth
analyses. For this investigation, Serial Dilution Test Method outlined in NACE TM0194-20041
was the method of choice bacteria growth analyses. Additional evidence includes metabolic
products, such as sulfides, obtained from fluid sampling and chemical analyses.
Table 2
Classification of general and pitting corrosion rates
General Corrosion Pitting Corrosion
Low < 1.0 mpy (< 0.0254 mm/y) Low < 5.0 mpy (0127 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 (0127-0.254 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)
Bacteria Population Density and MIC.
Consider, for example, a system that has been experiencing increased corrosion over a period
of time. If the trend of corrosion rate versus time parallels the corresponding trend of sessile
bacteria population density over that same period of time, the general assumption is to ascribe
the source of the corrosion to the prevailing sessile bacteria population density. It is because of
this pragmatic correlation that oil companies normally develop in-house guidelines for
quantifying bacteria proliferation. For example, the operator guideline for quantifying sessile and
planktonic bacteria proliferation is presented in Table 3.
Table 3
Target bacteria population density
Bacteria Type Sessile Bacteria Planktonic Bacteria
SRB <102 counts/cm2 <1 counts per ml
GAB <102 counts/cm2 <104 counts per ml
GAnB <102 counts/cm2 <104 counts per ml
The concern for MIC and for sulfate reducing bacteria in particular explains the adoption of a
stringent planktonic SRB target population density. Although the concern for MIC and biotic
population is justified, there is general agreement that there is only a tenuous correlation
between SRB population and corrosion rate. On the other hand, there is a strong correlation of
corrosion rates with the population of acid producing bacteria (APB). APB strains include aerobic
sulfur oxidizing bacteria, clostridium (obligate anaerobes), escherichia, klebsiella, etc.
(facultative anaerobes). The more APB there is, the more acid is produced, and the higher is the
9
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this paper are solely those of the author(s) and are not necessarily endorsed by the Association.
corrosion rate. The fact is that MIC is an electrochemical corrosion process and high sessile
APB density would have a more direct impact on the corrosion electrochemistry by lowering the
pH at the metal surface. The above guideline implies that the population of the different strains
of bacteria in an operating system should be kept under the target values. If the target values
are exceeded, then aggressive biocide treatment of the system is indicated. The target values
also provide a means of assessing the efficacy of the biocide treatment program and serve as a
basis for biocide dosage control. This approach admits the fact that it is nearly impossible to kill
all bacteria. Minimization, destabilization and/or regular disruption of biofilm activity provide the
key to mitigating MIC damage.
Although, the presence of planktonic microbes is indicative of the presence and type of sessile
microbes, it cannot provide the necessary proof for the effect of sessile bacteria population
density on corrosion, nor the effectiveness of biocide treatment. Biofilm matrix with its bacteria
community represent the primary source of MIC, planktonic bacteria population density is only
corroborative. Sessile bacteria, known to be responsible for MIC, are well protected by the matrix
of gelatinous extra-cellular polymeric substances (EPS) generally referred to as biofilms.
Corrosion, occasioned by sessile bacteria, is characterized by:
Microbial break down of passive metal film and the attendant corrosion cell
Microbial communities creating biofilms that could cause under-deposit corrosion
Microbial metabolic products that could cause pitting
Because biofilms are never completely destroyed by treatment chemicals, sessile bacteria
readily re-colonizes the system as long as nutrients are available. Consequently, the trick for
mitigating MIC is to continuously disrupt biofilm formation. If the biofilm-bound sessile bacteria
community is effectively disrupted, corrosion rates would be significantly reduced even if serial
dilution microbial culture indicates the presence of live offensive planktonic bacteria. On the
other hand, conditions that are friendly to biofilm formation are nearly impossible to eliminate in
the oil field, namely, nutrients, low velocity, particulate loading, scale formation, and water
stagnancy. The effects of selected environments on bacteria and corrosion in the oilfield are
summarized in Table 4.
Table 4
Effects of selected environment on bacteria and corrosion (DO = dissolved oxygen)
Effects of pH Effect of Dissolved Oxygen Effect of Ionic strength
Neutral pH
favors bacteria
growth.
Low pH
increases
corrosion.
High DO increases corrosion.
High DO supports GAB/APB
growth, which assists the
survival of other bacteria (SRB
and GAnB/APB) by symbiosis.
DO-free environment favors
SRB and GAnB/APB growth
High ionic strength (conductivity),
especially chloride, increases
corrosion.
High salt content slows bacteria
growth
Lower salt content favors bacteria
Under anaerobic conditions, SRB acts as a cathode by creating a galvanic couple with the iron
surface; the iron acts as an anode. The open circuit potential of the iron increases and moves to
more positive values as long as the SRB is active. Additionally, bacteria generally influence the
type and concentrations of ions, pH, and oxygen levels resulting in significant variations in the
chemical and physical characteristics of the environment thereby accelerating the corrosion
10
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process.
Relative Significance of Fluid Parameters Versus Bacteria Polpulation Density
Each fluid parameter could have significant importance depending on its capacity to reflect the
corrosion state of the system. Crude oil is classified into two categories based on water cut; the
water cut of dry crude is <5% and the water cut of wet crude is >5%. There is generally a lot
more water separation/accumulation in wet crude handling system than in the dry crude handling
system. In both cases, however, the accumulated water has several important fluid parameters
that could significantly affect corrosivity. Consequently, the fluid parameters, illustrated in Table
5, were analyzed but the results for the water samples from the wet and dry crude handling
systems were essentially similar. The results of the present study support the conclusion of an
earlier paper6 that there is no direct correlation of corrosivity severity with corrosion severity
under the present production scenarios. This conclusion was ascribed to a possible combination
of factors including the presence of a durable film layer of corrosion inhibitor, scale compounds,
and/or the presence of a passive layer of iron oxide, which negate the effects of fluid corrosivity.
The paper6 concluded that bacteria population is the key performance indicator in bacteria-
infected, MIC-susceptible water handling system.
Table 5
Fluid parameters wet and dry crude handling systems
S/N Parameter Significance
1 Water Cut An increase in water cut results in substantial water separation/
accumulation at low points, low fluid velocity, and dead ends.
2 pH A lower value of pH implies higher corrosivity (pH of <7 implies
acidity of the fluid).
3 Conductivity A high conductivity of the fluid generally implies high corrosivity.
4 Chloride Chloride acts as electrolyte in corrosion reactions. Corrosivity of
the fluid generally increases with an increasing chloride content.
5 Sulfate Sulfate acts as an electrolyte in corrosion reactions. Corrosivity
of the fluid generally increases with increasing sulfate content.
However, sulfate contributes less to corrosivity than chloride.
6 Hydrogen Sulfide
(H2S) H2S increases corrosivity of the fluid by providing H+ ions for the
corrosion cell.
7 Total Hardness As the hardness of the fluid increases, scaling tendency
increases. This may contribute to under-deposit corrosion.
8 Dissolved Oxygen
(DO)
High DO content is indicative of high corrosivity. Typically the
DO content is kept at <10 ppb by the use of oxygen
scavengers.
9 Dissolved Iron Dissolved iron content is a measure of corrosion. An increasing
trend of iron content might be indicative of increasing corrosion.
10 Total Iron Total iron is the sum of dissolved iron and insoluble iron oxides.
The difference between total and dissolved iron represents the
amount of oxides formed during corrosion.
11 Manganese (Mn) Manganese is a major alloying element in carbon steel. A high
manganese content in oilfield fluid is indicative of high
corrosion.
11
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12 Corrosion Inhibitor
(C.I.) Residual A high content of corrosion inhibitor residual implies decreased
corrosivity.
BACTERIA POPULATION DENSITY AS CORROSION CONTROL METRIC
Corrosion risk management for an operation is the systematic application of policies, practices,
and resources to control risk and provide reliable safeguards against unexpected failures and
leaks, occasioned by corrosion, which can jeopardize mechanical integrity, operation, health,
safety and environment (HSE). A corrosion control metric is a performance measure that can be
used to assess the efficiency of the prevailing corrosion risk management strategy5. For bacteria
population to be used as a corrosion control metric, some empirical correlation is required,
however fragile, that could relate bacteria population to corrosion.
Figures 1 to 8 (above) validate that the trend of the general and pitting corrosion rates are
impacted by sessile bacteria population density trend. The bacteria population is in turn impacted
by the water-cut that gives rise to water separation/accumulation, which enhances bacteria
growth. In spite of the preponderance of the data depicted in the figures, a distinct correlation is
not discernible, except for a rather tenuous relationship, between corrosion severity and bacteria
population density severity. To interpret the field data in terms of the corrosion severity
classification given in Table 2 as well as the target population density depicted in Table 3, we
resort to elementary statistics.
Corrosion and Pitting Incidents
A detailed study of the corrosion and pitting incidents in wet and dry crude handling systems
was performed by utilizing monitoring data from 2011 to 2013 from five (5) gathering centers.
For the wet and dry crude, the number of incidents of ‘Low’, ‘Moderate’, ‘High’, and ‘Severe’
corrosion is tabulated in Table 6. The location-wise categorization of High & Severe Corrosion
Incidents in Wet & Dry crude handling systems is presented in Table 7.
Table 6
Incidents of general and pitting corrosion in wet & dry crude
Fluid
Type
Incidents of General Corrosion Incidents of Pitting Corrosion
Low Moderate High Severe Low Moderate High Severe
Wet
Crude 652 64 34 31 632 21 39 89
Dry
Crude 187 10 6 2 182 6 9 8
The above data illustrate that general and pitting corrosion incidents are in greater numbers in
wet crude system than in dry crude system. Table 7
Location-wise categorization of high & severe corrosion incidents in wet & dry crude
Fluid Type
Incidents of High & Severe General
Corrosion Incidents of High & Severe Pitting
Corrosion
Tank bottom Other locations Tank bottom Other locations
Nos. % Nos. % Nos. % Nos. %
12
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Wet Crude 20 31 45 69 25 20 103 80
Dry Crude 7 88 1 12 14 82 3 18
Although, some of the streams labeled as wet crude actually had <5% water cut, the results for
the wet crude system established that corrosion is active, not only at wet tank bottoms, but also
at other locations, including wet crude manifold, wet header, wet separator, and de-salter.
Indeed, the coupons installed at tank bottoms and crude receiving headers are comparatively
less corroded than the coupons installed in other locations. This is due to the fact that water
separation/accumulation at other locations is significant. A corresponding analysis of high and
severe corrosion locations in dry crude reveal that the majority of the corrosion incidents occur
at the crude tank bottom where water separation/accumulation takes place.
Incidents of SRB, GAB, and GAnB
Sessile bacteria data of wet and dry crude handling systems in the gathering centers were
reviewed and Table 8 depicts the categorization of the results based on the number of incidents
(<102 counts/cm2) and (>102 counts/cm2) for SRB, GAB, and GAnB. The location-wise
categorization of the high bacteria incidents (>102 per cm2) are presented in Table-9.
Table 8
Incidents of bacteria in wet & dry crude
Fluid Type
Incidents for SRB Incidents for GAB Incidents for GAnB
<102
counts per
cm2
>102
counts per
cm2
<102
counts per
cm2
>102
counts per
cm2
<102
counts per
cm2
>102
counts per
cm2
Wet Crude 95 4 76 23 51 48
Dry Crude 14 2 13 3 12 4
Table 9
Location wise categorization of bacteria incidents in in wet & dry crude
Fluid
Type
Incidents for SRB>102
counts per cm2 Incidents for GAB>102
counts per cm2 Incidents for GAnB>102
counts per cm2
Tank bottom Other
locations Tank bottom Other
locations Tank bottom Other
locations
Nos.
%
Nos.
%
Nos.
%
Nos.
%
Nos.
%
Nos.
%
Wet
Crude 2 50 2 50 5 22 18 78 7 15 41 85
Dry
Crude 2 100 0 0 1 33 2 67 2 50 2 50
Comparing all locations in the dry crude handling system, the percentage of high bacteria
incidents at the tank bottom is relatively higher compared to the situation in the wet crude
handling system. This is not unexpected as the tank bottom of the dry crude handling system is
essentially the only location where water separation/accumulation occur providing viable
13
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this paper are solely those of the author(s) and are not necessarily endorsed by the Association.
conditions for bacterial growth and MIC. In the case of wet crude, there is possibility of water
separation/accumulation at all locations other than tank bottom, which provide viable
environment for bacterial growth and MIC.
Asset Integrity Risk Assessment and Prioritization
According to API 580-20027, relative risk is the comparative risk of one system to another and
the establishment of relative risk is the key to prioritization. This entails the comparative risk
analysis of a system in a facility to a similar system in order to differentiate and provide a relative
priority for integrity assessment. Risk-based inspection (RBI) is focused on a systematic
determination of relative risks. RBI concept is focused on inspection, but inspection and
monitoring are the two key processes by which the onset of internal corrosion, external corrosion
and stress corrosion cracking can be detected. If inspection techniques are used to measure
corrosion rates, significant measurable corrosion (about 10 mils or 0.254 mm) has to occur to
the base materials, before it can be detected. That loss of base metal is normally irreplaceable
and the loss will have an effect upon all subsequent MAOP (maximum allowable operating
pressure), structural integrity, and remaining life calculations. On the other hand, corrosion
monitoring is able to detect corrosion significantly quicker (less than 1.0 mil equal to 0.0254 mm).
This “early detection” of the onset of corrosion enables a quick response to the changing
operational environment, and, when appropriate, enables increasing the quantity of treatment
chemicals applied to the process fluids, thereby enhancing protection. Thus, corrosion
monitoring helps to minimize the extent of damage to the base metal and helps to maintain the
structural integrity of the production systems.
Risk assessment process identifies the conditions that could lead to asset failure. Risk,
understood in its technical sense, is a combination of the probability that an event will occur and
the consequences of the occurrence. When probability and consequence are expressed
numerically, risk is the product. For wet and dry crude oil handling systems, the leak impact
factor, representing the consequence, is essentially identical. Hence the risk factor is highest
for the crude oil handling system that has the highest probability of negative outcome occasioned
by bacteria population. That is, the probability of failure could be used as a surrogate to establish
a relative risk ranking for maintenance action. This enables the framing of the bacteria impact
question in terms of probability. That is, which of the wet and dry crude oil handling systems has
the highest probability of failure, and therefore the highest relative risk, of negative outcome
occasioned by bacteria population and the attendant corrosion?
The data presented in Tables 6, 7, 8, and 9 essentially establish an asset integrity risk ranking
for the wet and dry crude oil handling systems under study. Based on the tabulated data, the
corrosion risk of wet and dry crude oil handling systems decreases in the following order:
Wet Crude > Dry Crude
Within the wet crude oil handling system, the risk to each location is in the following decreasing
order:
Wet Crude Tank Bottom > Wet Crude Header > Wet Crude Separator Outlet
Within the dry crude oil handling system, the risk to each location is in the following decreasing
order:
14
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Dry Crude Tank Bottom > Dry Crude Header > Dry Crude Separator Outlet
With this prioritization scheme, inspection activities may be deployed to confirm whether actual
damage has occurred. When appropriate, mitigation actions may be deplored thereby enhancing
asset integrity. That is, the scheme is within the realm of corrosion risk management, namely,
the identification, assessment, and prioritization of risks followed by coordinated and systematic
application of policies, practices, and resources to minimize the impact of corrosion. The scheme
assists corrosion risk criticality assessment, helps to ensure reliability of production, and enables
the avoidance of losses from operational failures.
SUMMARY AND CONCLUSION
1 The wet crude handling system is characterized by high and severe corrosion than
the dry crude handling system. This correlates with the overall incidents of bacterial
species studied
2 For both wet and dry crude handling systems, the highest corrosion incidents occur at
tank bottoms..
3 For both wet and dry crude handling systems, the severity of pitting corrosion is higher
than general corrosion, although the effect is more pronounced in wet Crude.
4 For both wet and dry crude handling systems, matrixes of gelatinous extra-cellular
polymeric substances (biofilms) are observed on scale and corrosion coupons along
with pitting corrosion, particularly at tank bottoms.
5 The effect of bacteria population density on general and pitting corrosion establishes
an asset integrity risk ranking for wet and dry crude handling systems. The risk to wet
and dry crude handling systems is in the following decreasing order:
Wet Crude > Dry Crude
6 Within both wet and dry crude handling systems, the location-specific risk is in the
following decreasing order:
Crude Tank Bottom > Crude Header > Crude Separator Outlet
REFERENCES
1. Field Monitoring of Bacteria Growth in Oil and Gas Systems, NACE International, NACE
TM0194-2014
2. Preparation, Installation, Analysis, and Interpretation of Corrosion Coupons in Oilfield
Operations, NACE International, NACE SP0775-2013.
3. ASTM G1 – 03, “Standard Practice for Preparing, Cleaning, and Evaluating Corrosion
Test Specimens,” American Society for Testing and Materials, PA, 2003
4. O. Olabisi. “Corrosion Rate as Key Performance Indicator in the North Slope”. Material
Performance, 52, 8, 50-54 (2013)
5. A. Jarragh, S. Al-Sulaiman, Olagoke Olabisi, A. Al-Mutairi. “Ribosomal RNA
Characterization of Bacteria: Linkage with Field Data Based on Culture Media”.
CORROSION/2015, Paper No. C2015-5591, (Dallas, TX: NACE 2015)
6. Olagoke Olabisi, A. Jarragh, Y. Khuraibut, A. Mathew. “Identifying Key Performance
Indicators for Corrosion in Oilfield Water Handling Systems”. CORROSION/2014, Paper
No. C2014-4348, (San Antonio, TX: NACE 2014)
15
©2015 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, 15835 Park Ten Place, 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.
7. API RP 580 - Risk Based Inspection, Second Edition, November 2009.
16
©2015 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, 15835 Park Ten Place, 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.
ResearchGate has not been able to resolve any citations for this publication.
Full-text available
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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.
Full-text available
Conference Paper
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.
Full-text available
Article
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.
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
Identifying Key Performance Indicators for Corrosion in Oilfield Water Handling Systems
  • A Olagoke Olabisi
  • Y Jarragh
  • A Khuraibut
  • Mathew
Olagoke Olabisi, A. Jarragh, Y. Khuraibut, A. Mathew. "Identifying Key Performance Indicators for Corrosion in Oilfield Water Handling Systems". CORROSION/2014, Paper No. C2014-4348, (San Antonio, TX: NACE 2014) 15