ArticlePDF Available

Ranking asset integrity risk of oilfeld water handling systems

Authors:
  • Infra-Tech Consulting LLC

Abstract and Figures

Microbiologically influenced corrosion is the degradation of a material under the influence of environmental factors complicated by the metabolic activities of microorganisms. Microbiological attack on process equipment used in the petroleum industry results in increased operating expenses and reduced income.
Content may be subject to copyright.
58 DECEMBER 2017 MATERIALS PERFORMANCE NACE INTERNATIONAL: VOL. 56, NO. 12
CM
CORROSION MANAGEMENT
W
Microbiologically inuenced corro-
sion is the degradation of a material
under the inuence of environmental
factors complicated by the metabolic
activities of microorganisms. Microbi-
ological attack on process equipment
used in the petroleum industry results
in increased operating expenses and
reduced income.
When equipment experiences degrada-
tion from microbiologically influenced
corrosion (MIC), the elements for a corro-
sion cell are normally present before the
microbes (chiefly bacteria and fungi)
become involved in the corrosion process.
Conditions that support microbial corro-
sion will often lead to corrosion even in
the absence of microbes; however, the
presence and activity of microorganisms
significantly accelerate the corrosion
process.
A biofilm that comprises the microor-
ganisms involved in the corrosion process
is held in place by a matrix of gelatinous
extra-cellular polymeric substances (EPS),
which is generally referred to as slime. Cor-
rosion is accentuated by the related activi-
ties of the microorganisms, and the build-
up of their metabolic products in the slime
has a significant influence on the nature
and type of metal loss taking place (i.e.,
MIC is a process sustained by the condi-
tions favoring biofilm formation).
Field Data
At Kuwait Oil Co., microbial corrosion
activity predominates in the following
water systems: seawater, brackish water,
effluent water, recycle water, and firewater.
A monitoring strategy for these water sys-
tems facilitates the identification of the
prevailing bacteria and the implementa-
tion of corrosion mitigation measures. To
achieve effective bacteria monitoring,
monitoring devices are placed in the areas
where the buildup of biofilms—and hence,
sessile (attached) bacteria growth—are
expected to occur.
As part of the monitoring process, the
monitoring crew retrieves the bioprobes
and weight-loss coupons and recovers ses-
sile bacteria samples from their surfaces.
For unpiggable pipelines, routine corrosion
and sessile bacteria monitoring are con-
ducted using strip weight-loss coupons.
Planktonic ( floating) bacteria surveys are
carried out by collecting liquid samples
from tanks, vessels, wellheads, and pipe-
lines through sample valves. Aside from
identifying the type of bacteria present,
planktonic bacteria surveys expose the pri-
mary bacteria sources in an operation. Bac-
teria growth analyses and interpretation
for sulfate-reducing bacteria (SRB), general
aerobic bacteria (GAB), and general anaer-
obic bacteria (GAnB) are performed based
on the serial dilution test method outlined
in NACE TM0194-2014.1
On the other hand, certain morphology
of corrosion pits is sometimes interpreted
Ranking Asset Integrity Risk
of Oileld Water Handling
Systems
olaGoKe olabisi, DNV-GL, Ahmadi,
Kuwait
abdul RaZZaG al-shamaRi,
saleh al-sulaiman, ameR JaRRaGh,
and ashoK mathew, Kuwait Oil Co.,
Ahmadi, Kuwait
59NACE INTERNATIONAL: VOL. 56, NO. 12 MATERIALS PERFORMANCE DECEMBER 2017
as a sign of MIC. For example, a terraced pit
is accepted as indicative of SRB, but pits
within pits and/or tunneling is accepted as
indicative of GAB. Because such morpholo-
gies could be explained in terms of abiotic
mechanisms as well, corroboration is nor-
mally sought for biotic mechanisms based
on microbe growth analyses. Additional evi-
dence for biotic mechanisms may include
sampling for metabolic products such as
sulfides. In this work, DNA sequence analy-
sis is not performed and the bacteria are
not identified to the genus or species level
by means of recombinant DNA sequencing.
Following removal, coupons are
cleaned using chemicals or glass-bead
blasting. Weight loss is measured for corro-
sion rates and pit depth is measured with a
microscope to determine pitting rates.
Coupon corrosion rates are determined
using NACE SP0775-2014,2 while coupon
processing methodology follows ASTM
G1–03.3 The data are grouped in a database
according to the fluid type so that the cor-
rosion trends can be easily discerned in a
particular fluid. Coupons are photo-
graphed for later review and the digital
photographs are archived in a database.
The used coupons are placed in treated
envelopes and saved. Table 1 shows the cor-
rosion severity classification according to
NACE SP0775-2014 in terms of corrosion
rates in mpy or mm/y.
Bacteria Population Density
and Microbiologically
Influenced Corrosion
Consider, for example, a system that
has been experiencing increased corrosion
over time. If the trend for corrosion rate vs.
time parallels the corresponding plot of
sessile bacteria population density over
that same time period, the general assump-
tion is to ascribe the source of the corro-
sion to the prevailing sessile bacteria popu-
lation density. Figure 1 illustrates a
five-year trend (from 2007 to 2011) for bac-
teria count and general corrosion rate for
the recycle water system, and Figure 2
shows the trend for bacteria and pitting
corrosion rate for the same time period for
the recycle water system. Similar plots for
TABLE 1. CLASSIFICATION OF GENERAL AND PITTING CORROSION
RATES (NACE SP0775-2013)
General Corrosion
(1 mpy = 0.0254 mm/y)
Pitting Corrosion
(1 mpy = 0.0254 mm/y)
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)
FIGURE 2 Trend of bacteria count and pitting corrosion rate in recycle water system
(1 mpy = 0.0254 mm/y).
FIGURE 1 Trend of bac teria count an d general corrosion ra te in the recycl e water system
(1 mpy = 0.0254 mm/y).
60 DECEMBER 2017 MATERIALS PERFORMANCE NACE INTERNATIONAL: VOL. 56, NO. 12
CM
CORROSION MANAGEMENT
seawater, brackish water, effluent water,
and firewater are available.4
Because of this pragmatic correlation,
oil companies normally develop in-house
guidelines for quantifying bacteria prolif-
eration. For example, the Kuwait Oil Co.
guidelines for quantifying sessile and
planktonic bacteria proliferation are pre-
sented in Table 2. These guidelines imply
that the populations 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 bio-
cide treatment of the system is indicated.
The target values also provide a means of
assessing the efficacy of the biocide treat-
ment program and serve as a basis for bio-
cide dosage control. This approach admits
the fact that it is nearly impossible to kill all
bacteria. Minimization, destabilization,
and/or regular disruption of biofilm activ-
ity provide the key to preventing significant
MIC damage.
Although the presence of planktonic
populations is indicative of the presence
and type of sessile bacteria populations, it
cannot provide proof of the effect that the
sessile bacteria population density has on
corrosion or the effectiveness of the biocide
treatment. That is, a biofilm matrix with its
bacteria community represents the pri-
mary cause of MIC, while planktonic bacte-
ria population density is only corrobora-
tive. Sessile bacteria, which are responsible
for MIC, are well-protected by EPS. Corro-
sion occasioned by sessile bacteria is char-
acterized by:
TABLE 2. TARGET BACTERIA POPULATION DENSITY
Bacteria Type Sessile Bacteria Planktonic Bacteria
SRB <102 counts/cm2<1 counts per mL
GAB/APB <102 counts/cm2<104 counts per mL
GAnB <102 counts/cm2<104 counts per mL
TABLE 3. NUMBER OF CORROSION INCIDENTS CATEGORIZED PER TABLE 2
Fluid
Type pH
Dissolved
Oxygen
(ppb)
Total Dissolved
Solids (mg/L)
Incidents for General Corrosion Incidents for Pitting Corrosion
Low Moderate High Severe Low Moderate High Severe
Brackish 6.0-7.5 10-3,000 5,000-18,000 1 7 11 17 0 0 0 32
Recycle 5.5-7.0 10 6,000-20,000 13 5 6 10 0 0 3 25
Efuent 5-6.5 10 45,000-50,000 4 2 3 13 0 0 2 24
Seawater 6-7.5 10 40,000-45,000 923 5 3 9 3 5 13
Microbial breakdown of the metal’s
passive film and acceleration of the
corrosive attack
Microbial communities (biofilms)
that can cause underdeposit corro-
sion (UDC)
Microbial metabolic products that
can cause pitting
Because biofilms are never completely
destroyed by treatment chemicals, sessile
bacteria readily recolonize the system if
and when nutrients are available. Conse-
quently, the trick for mitigating MIC is to
continuously disrupt biofilm formation. If
the EPS-bound sessile bacteria community
is effectively disrupted, corrosion rates
would be significantly reduced even if the
serial dilution microbial culture indicates
the presence and type of live planktonic
bacteria. On the other hand, conditions
that are friendly to biofilm formation are
nearly impossible to eliminate in oilfield
water systems (i.e., nutrients, low velocity,
particulate loading, scale formation, and/
or water stagnancy).
In addition, the presence of oxygen
accelerates MIC of iron, leading to the con-
version of the primary iron sulfide product,
mackinawite (FeS), to pyrite (FeS2) and
elemental sulfur.5 In the absence of oxygen,
anaerobic SRB create a galvanic couple—
with the iron surface acting as a cathode
and the bio-fouled iron surface as an anode.
The open circuit potential of the iron
increases and moves to more positive val-
ues if the bacteria are active. In general,
microbes influence the type and concen-
trations of ions, pH, and oxygen levels,
which results in significant variations in
the chemical and physical characteristics
of the fluid environment and, thereby,
accelerates the corrosion rate.
Bacteria Population Density
as a Corrosion Control Metric
Corrosion risk management for an
operation is the systematic application of
policies, practices, and resources to control
corrosion risk and provide reliable safe-
guards against unexpected failures and
leaks caused by corrosion that can jeopar-
dize mechanical integrity, operation,
health, safety, and the environment. A cor-
rosion control metric is a performance
measure that can be used to assess the effi-
ciency of the prevailing corrosion risk man-
agement strategy.6 For bacteria population
to be used as a corrosion control metric,
some empirical correlation is required,
however tenuous, that could relate bacte-
ria population to corrosion.
Figures 1 and 2 validate that the trends
for general and pitting corrosion rates are
impacted by the sessile bacteria population
density trend. However, a distinct correla-
tion is not discernable—not only for the
recycle water data shown in Figures 1 and
2, but for the data corresponding to all the
other water handling systems as well.4 To
interpret the field data in terms of the cor-
rosion severity classification given in Table
1, as well as the target population density
depicted in Table 2, elementary statistical
analysis was adopted for the five years’
worth of data. For each of the oilfield water
handling systems studied, the number of
corrosion incidents classified as “Low,
“Moderate,” “High,” and “Severe” for the
five-year period is summarized in Table 3.
The corresponding number of bacteria
incidents (<102 counts/cm2 and >102
61NACE INTERNATIONAL: VOL. 56, NO. 12 MATERIALS PERFORMANCE DECEMBER 2017
counts/cm2) for SRB, GAB, and GAnB in
each fluid type is presented in Table 4.
Asset Integrity Risk Ranking
The risk assessment process identifies
the conditions that could lead to asset fail-
ure. Risk, understood in its technical sense,
is the product of the probability that an
event will occur and the consequences of
the occurrence, when probability and con-
sequence are expressed numerically. The
leak impact factor, which represents the
consequence for each of the oilfield water
handling systems, is essentially identical.
Hence the risk factor is highest for the oil-
field water handling systems that have the
highest probability of a negative outcome
triggered by bacteria population.
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 oilfield water handling sys-
tems has the highest probability of failure
and, therefore, the highest relative risk of a
negative outcome due to bacteria popula-
tion and the accompanying corrosion?
According to API 580-2002,7 relative risk
is the comparative risk of a system to other
systems, and establishing relative risk is
the key to prioritization. This entails creat-
ing a comparative risk analysis of a system
in a facility vs. a similar system so the sys-
tems can be differentiated and a relative
priority for integrity assessment can be
established.
Risk-based inspection focuses on a sys-
tematic determination of relative risks, and
this concept is hinged on inspection; how-
ever, both inspection and monitoring are
the key processes for detecting the onset of
internal corrosion, external corrosion, and
stress corrosion cracking. If inspection
techniques are used to measure corrosion
rates, significant measurable corrosion
(~10 mils [0.254 mm]) must occur to the
base material before it can be detected.
That loss of base metal is normally irre-
placeable, and will inf luence all subsequent
maximum allowable operating pressures,
structural integrity, and remaining life cal-
culations. On the other hand, corrosion
monitoring can detect corrosion signifi-
cantly faster. The 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 maintain the
structural integrity of the production
systems.
Conclusions
The data presented in Tables 3 and 4
essentially establish an asset integrity risk
ranking for the four oilfield water handling
systems under study. Each system is ranked
by decreasing risk, as follows: brackish
water > seawater > recycle water > eff luent
water.
This prioritization scheme is within the
realm of corrosion risk management,
namely, the identification, assessment, and
prioritization of risks followed by the coor-
dinated and systematic application of poli-
cies, practices, and resources to minimize
the impact of corrosion. With this scheme,
inspection activities may be deployed to
TABLE 4. NUMBER OF BACTERIA INCIDENTS CATEGORIZED PER TABLE 3 (i.e., OPERATOR TARGET BACTERIA
POPULATION DENSITY)
Fluid Type
Dissolved
Oxygen (ppb)
Total Dissolved
Solids (mg/L)
Incidents for SRB Incidents for GAB Incidents for GAnB
<102 per
cm2
>102 per
cm2
<102 per
cm2
>102 per
cm2
<102 per
cm2
>102 per
cm2
Brackish 10-3,000 5,000-18,000 327 030 030
Recycle 10 6,000-20,000 13 12 718 718
Efuent 10 45,000-50,000 18 216 4 9 11
Seawater 10 40,000-45,000 12 20 11 21 527
confirm whether irreversible damage has
occurred. If appropriate, mitigation actions
may be implemented, thereby enhancing
asset integrity. The key benefit is assistance
with assessing the criticality of the corro-
sion risk, reliability of production, and
avoidance of losses from possible opera-
tional failures.
Acknowledgment
The support of Kuwait Oil Co. is hereby
acknowledged.
References
1NACE TM0194-2014, “Field Monitoring of
Bacteria Growth in Oil and Gas Systems”
(Houston, TX: NACE International, 2014).
2NACE SP0775-2013, “Preparation, Installa-
tion, Analysis, and Interpretation of Corro-
sion Coupons in Oilfield Operations” (Hous-
ton, TX: NACE, 2013).
3ASTM G1–03, “Standard Practice for Prepar-
ing, Cleaning, and Evaluating Corrosion Test
Specimens” (West Conshohocken, PA: ASTM,
2011).
4A.R. Al-Shamari, et al., “Developing a Metric
for Microbiologically Influenced Corrosion
(MIC) in Oilfield Water Handling Systems,
CORROSION 2013, paper no. 2299 (Houston,
TX: NACE, 2013).
5H.A. Videla, L.K. Herrera, “Influence of
Microorganisms on the Corrosion and
Protection of Metals: An Overview,
CORROSION 2011, paper no. 11218 (Hous-
ton, TX: NACE, 2011).
6O. Olabisi, “Use of Corrosion Rate as Key
Performance Indicator (KPI) in the North
Slope,MP 52, 8 (2013).
7API RP 580, “Risk Based Inspection, Second
Edition” (Washington, DC: API, 2009).
Contin ued on page 62
Ranking Asset Integrity Risk of Oilfield Water Handling Systems
Article
Full-text available
Microbiologically influenced corrosion is the degradation of a material under the influence of environmental factors complicated by the metabolic activities of microorganisms. Microbiological attack on process equipment used in the petroleum industry results in increased operating expenses and reduced income. This article discusses treatment options for various production streams to prevent corrosion and downtime of assets.
Conference Paper
Full-text available
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
Article
Full-text available
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.
Article
Microorganisms are able to drastically change the electrochemical conditions at the metal/solution interface by biofilm formation including bacterial consortia and extracellular polymeric substances (EPS) as the main components. The presence of biofilms generally facilitates the initiation of localized corrosion but this effect can be reversed to corrosion inhibition. Microbial corrosion inhibition and its counter process, microbiologically influenced corrosion (MIC) are rarely linked to a single mechanism or to a single species of microorganisms. In recent years microbial inhibition of corrosion and protection of metals have been attributed to the blocking effect of biofilms and EPS. However, this simplistic approach must be discussed from an electrochemical point of view to understand the complex metal-microbe interactions at the metal surface. With this aim, several practical cases involving sulfate-reducing bacteria (SRB) and other microorganisms are critically discussed. General mechanisms for interpreting the influence of microorganisms on the protection and passivity of metals are presented.
Developing a Metric for Microbiologically Influenced Corrosion (MIC) in Oilfield Water Handling Systems
  • R Shamari
.R. Al-Shamari, et al., "Developing a Metric for Microbiologically Influenced Corrosion (MIC) in Oilfield Water Handling Systems, " CORROSION 2013, paper no. 2299 (Houston, TX: NACE, 2013).
Risk Based Inspection, Second Edition
  • Api Rp
API RP 580, "Risk Based Inspection, Second Edition" (Washington, DC: API, 2009).