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Internal Corrosion of Pipelines: Mechanism, Modeling and Management
Frank Cheng
ICorr Aberdeen Branch 2021-22 Technical Events Oct. 26, 2021
Acknowledgements
The City of
Calgary
▪ The fourth
largest city in
Canada, Calgary
is the hub of
oil/gas and
pipeline industry
in the world.
Banff National Park
90 km
The University of Calgary
Cheng Laboratory for Research in Pipeline Corrosion, Integrity and New Energy Transmission Technology
Pipelines for oil/gas transmission
Pipelines for effective and economic transmission of new energies, contributing to the net-zero target
Types of pipelines
Today’s talk focuses on upstream gathering pipelines
Internal corrosion is the most important mechanism causing failure of upstream pipelines
Alberta Energy Regulator (AER), Pipeline Performance in 2019,Calgary, Canada, Jul. 2020.
Internal corrosion of pipelines is a complex phenomenon.
12
Multiple factors affecting
the corrosion processes
❖ Fluid chemistry
▪ CO2/H2S partial pressure, solution pH, salts, organic acids (acetic acid), oil phase, solid particles, etc.
❖ Operating condition
▪ Temperature, pressure, flow velocity, fluid hydrodynamics, etc.
❖ Pipe geometry
▪ Pipe size, inclination, elbow/bent, etc.
Chemical reactions:
Electrochemical
anodic reactions:
Electrochemical cathodic reactions:
Multiple reactions occurring at the same time
Film formation:
Thermodynamics of pipeline internal corrosion
▪ Evaluate corrosion likelihood under given conditions and determine the dominant partial reactions.
▪ For chemical reactions, derive the reaction equilibrium constants.
▪ For electrochemical reactions,
— calculate standard electrode potentialsby Gibbs free energy.
— determine partial reaction potentials by Nernst equation.
CO2 corrosion thermodynamic
model
Critical role of fluid hydrodynamics (pipe flow)
For corrosion of a straight pipe
Critical role of fluid hydrodynamics (impingement)
For corrosion at elbow
Inhibitive effect of oil phase
Erosive effect of solid sands
Effect of organic acid
No acetic acid
0.02 M acetic acid
Pitting corrosion under FeCO3 scale
In oilfeild formation
water purged with
99.95% CO2 at 600C
48 h
120 h
The galvanic coupling effect between the scale-covered steel and bare steel at pores results in pitting corrosion.
240 h
Internal pitting corrosion under sand bed
Pitting corrosion under sand bed and its modeling for prediction of pit growth
Internal microbial corrosion of pipelines
▪ In oil/gas industry, microbial corrosion has caused ~ 40% of all internal corrosion events in pipelines.
Internal microbial corrosion under deposit
▪ Unique corrosive environments: Deposit of a mixture of petroleum sludge, sands, water, microorganism, corrosion products, etc.
▪ A dual role of the deposit in limited supply of nutrients to bacteria and reduced disturbance to the biological environment
▪ Essential factors: Fluid flow, and porosity of the deposit
Gas pipelines: Internal microbial corrosion
▪ Unique corrosive environments:
—A thin layer of electrolyte (or condensate water)
▪ Formation of a complete biofilm usually hard
▪ Deposit of corrosion products
▪ Essential factor: Electrolyte layer thickness
▪ It will affect bacterial adhesion, corrosion reaction mechanisms, corrosion product film, corrosion rate
▪ Difficulty in testing: Reproduce the thin electrolyte layer containing bacteria and the formed biofilm
Internal corrosion in water condensate
Evans ring and three-phase boundary (TPB) zone theory
CFD modeling of oil-H2O flow for pipeline corrosion prediction
0.2 m/s 1.0 m/s
0.2 m/s 1.0 m/s
0.2 m/s 1.0 m/s
CFD modeling of oil-H2O flow for pipeline corrosion prediction
The oil content less than 60%:
The oil content exceeds 70%:
Water chemistry model for pipeline
corrosion prediction
▪ Solution pH is critical for calculation of corrosion rate in CO2 corrosion model.— Sampling of solution for
pH measurements is usually difficult, and moreover, the measuring results deviate from the actual values.
Validation of water chemistry modeling results
100 200 300 400 500 6002.6
2.8
3.0
3.2
3.4
3.6
pH
pCO2
(bar)
Model of Duan and Li 0m NaCl
Model of Duan and Li 2m NaCl
This model 0m NaCl
This model 2m NaCl
0 50 100 150 200 250 300 3502.9
3.0
3.1
3.2
3.3
3.4
3.5
3.6
3.7
3.8
3.9
pH
pCO2
(bar)
This model
Crolet and Bonis' model *
Exp. data by Meyssami et al.
0 1 2 3 4 53.5
3.6
3.7
3.8
3.9
4.0
pH
NaCl concentration (mol/L)
This model
Shell model **
Model of Plennevaux et al.
Exp. data of Hinds et al.
0.1 1 10 1000.1
1
10
100P
red
icte
d c
orr
osio
n r
ate
Measured corrosion rate
Water chemistry model for corrosion
prediction
▪ Comparison of the corrosion rate of X65 steel determined by weight-loss testing with the predicted results by the developed model
A finite element-based multi-physics field coupling model
Bulk solution
Iron carbonate scale
Steel
(1) Fluid hydrodynamic sub-model
(Navier-Stokes equations )
(2) Mass-transfer sub-model
(Nernst-Planck equation)
(3) Electrochemical corrosion sub-model
(Butler-Volmer equation)
0= V
FVpVVt
V++−=+
2)(
Correction factors:
▪ Porosity of corrosion scale
▪ Erosive effect of sands
▪ Bacterial accelerating effect
Modeling for pipeline CO2corrosion rate
Model
0 1 2 3 4 5 6 7 8 9 10 110.0
0.2
0.4
0.6
0.8
1.0
1.2
Co
rro
sio
n r
ate
(m
m/y
ea
r)
Flow velocity (m/s)
20 oC
30 oC
40 oC
50 oC
60 oC
pH=5, pCO2=10000 Pa
pH = 5, pCO2 = 10,000 Pa pH = 5, T = 20oC
Internal corrosion management
▪ Internal corrosion models
— Locate corrosion occurrence, especially pitting and erosive corrosion
— Predict corrosion rate
— Predict pitting growth rate
▪ Corrosion mitigation and control
— Periodic pigging to clean deposit/sludge
— The performance of inhibitors/biocides is not satisfactory
Internal corrosion direct assessment (ICDA)
Pre-assessment
Indirect inspection
Direct inspection
Post-assessment
Model
Pipeline internal corrosion: Mechanisms, modeling and management
