Research Papers: Pipeline Systems

A Framework for Risk-Based Integrity Assessment of Unpiggable Pipelines Subject to Internal Corrosion

[+] Author and Article Information
Carlos Melo, Ronald J. Hugo

Schulich School of Engineering,
University of Calgary,
Calgary, ABT2N 1N4, Canada

Markus R. Dann

Schulich School of Engineering,
University of Calgary,
Calgary, ABT2N 1N4, Canada
e-mail: mrdann@ucalgary.ca

Alberto Janeta

Departamento de Mantenimiento Petroamazonas,
EP Quito 170504, Ecuador
e-mail: Alberto_Janeta@petroamazonas.gob.ec

1Corresponding author.

Contributed by the Pressure Vessel and Piping Division of ASME for publication in the JOURNAL OF PRESSURE VESSEL TECHNOLOGY. Manuscript received September 24, 2018; final manuscript received December 12, 2018; published online February 21, 2019. Assoc. Editor: Bostjan Bezensek.

J. Pressure Vessel Technol 141(2), 021702 (Feb 21, 2019) (13 pages) Paper No: PVT-18-1207; doi: 10.1115/1.4042350 History: Received September 24, 2018; Revised December 12, 2018

Many pipelines are unpiggable, which means they cannot be examined by in-line inspections (ILI). Existing industry practice for integrity assessment of unpiggable pipelines is not risk based, which precludes optimal allocation of inspection and maintenance resources. A framework for risk-based integrity assessment of unpiggable pipelines subject to internal corrosion is presented. The framework considers localized corrosion and microbiologically influenced corrosion (MIC) by combining flow and corrosion analysis for probability and consequence analysis as part of a quantitative risk analysis. Primary results of the application of the proposed framework show that it is applicable and beneficial for inspection and maintenance cost optimization.

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Grahic Jump Location
Fig. 1

Distribution of causes of 16,489 pipeline failures from 1990 to 2012 in Alberta, Canada. Internal corrosion, material failure, and external corrosion are three most common failure causes.

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Fig. 2

Overview of pipeline system integrity management program process according to CSA Standard Z662 [17]. The implementation of this program is normative for sour service pipelines. The program includes risk identification, risk assessment, and risk control. Risk is controlled by the implementation of inspection and maintenance plans.

Grahic Jump Location
Fig. 3

Electrochemical corrosion cell in a pipeline. Anode, cathode, and metallic path are in the pipeline steel while the electrolyte is the water. Corrosion will not occur if water is not present [34].

Grahic Jump Location
Fig. 4

Increased flow velocity V3 > V2 > V1 reduces the thickness of the mass transfer boundary layer δ3 < δ2 < δ1 facilitating the transport of hydrogen ions from the bulk fluid to the metal and the removal of iron ions from the metal to the electrolyte. The increase in hydrogen ions at the metal surface and the removal of iron ions accelerates the consumption of electrons and the corrosion process [34].

Grahic Jump Location
Fig. 5

Overview of the risk management process for oil and gas pipelines according to CSA Z662 [17]. The process includes the risk assessment where the risk is quantified and evaluated in terms of acceptability and the risk control to reduce the risk in accordance to public and regulatory requirements.

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Fig. 6

Framework for risk-based integrity assessment of unpiggable pipelines alongside specific parts of a risk management process according to CSA Z662 [17]

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Fig. 7

Flow analysis to estimate variables that are required by the corrosion analysis to calculate the size of corrosion features [36,37] and by the consequence analysis to calculate the amount of fluids discharged for a leak or burst. The analysis is discretized in space and time to reduce the errors in the corrosion and consequence analysis.

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Fig. 8

Corrosion analysis to estimate the distribution of the size of localized corrosion features. The probabilistic corrosion model is utilized to include the temporal uncertainty of the corrosion process in the estimation of the size of general corrosion features. The population effect is also considered as part of the extreme value analysis [58].

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Fig. 9

Probability analysis for unpiggable pipelines subject to internal corrosion. The distributions of the size of localized corrosion features and the actual wall thickness are compared to estimate the PF for leak. The PF for burst is calculated by multiplying the PF for leak times a multiplication factor from pipeline failure data in Alberta, Canada [9].

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Fig. 10

Consequence analysis to calculate the consequence of failure for leak and burst. In the analysis, human, environmental, and economic consequences are considered [17].

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Fig. 11

Risk estimation is performed in the framework for leak and burst failure modes. In the risk evaluation, the safety of the pipeline is verified by comparison with the RAC [17].

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Fig. 12

Risk control is implemented using RBI and RBM planning. The results of the inspections are used to update the fluid and corrosion analysis and the system state after the repair is used to update the probability analysis. The risk-based optimization allows to modify the RAC [51].

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Fig. 13

Preposterior decision analysis (RBI) is used to select the number, location, and time for the inspections. Posterior decision analysis (RBM) allows to select the number, type, location, and time for the maintenance actions. RBI and RBM planning facilitate the optimization of the inspection and maintenance costs by identifying the inspection and maintenance strategies that minimize the total costs.

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Fig. 14

Risk monitoring allows the selection of the best locations and devices for internal corrosion monitoring. Risk is reduced in addition to risk control using risk mitigation that facilitates the improvement of internal corrosion mitigation plans as well as leak detection systems, and emergency response plans.

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Fig. 15

Top figure shows the probability of failure (black dotted line), consequence of failure (red dashed line), and RF (continuous blue) for each section at the end of year five. The RAC is also shown as a green dash-dot line. The highest risk section is Section One shown as yellow circle in the top figure. The bottom figure shows the elevation profile along with the depth of general corrosion predicted at the end of year five; here also, the locations selected for the inspection according to the DA practices are shown as yellow circles [22].

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Fig. 16

Optimum maintenance plan for scenario with 80 wt % for section one at year 2 according to RBM planning. The high inspection results require an earlier replacement of all sections between years five and seven.



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