Mechanism and Modeling of Internal Corrosion of Oilfield

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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

Thank You!

Contact: Prof. Frank Cheng, +1 (403)220-3693, fcheng@ucalgary.ca

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