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Research Papers: Pipeline Systems

Probabilistic Methods for Predicting the Remaining Life of Offshore Pipelines

[+] Author and Article Information
Alireda Aljaroudi

Safety and Risk Engineering Group,
Faculty of Engineering and Applied Science,
Memorial University,
St. John's, NL A1B 3X5, Canada
e-mail: aaa515@mun.ca

Premkumar Thodi

INTECSEA Canada,
WorleyParsons Group,
St. John's, NL A1C 6C9, Canada
e-mail: Premkumar.Thodi@intecsea.com

Ayhan Akinturk

National Research Council,
St. John's, NL A1B 3T5, Canada
e-mail: ayhan.akinturk@nrc-cnrc.gc.ca

Faisal Khan

Safety and Risk Engineering Group,
Faculty of Engineering and Applied Science,
Memorial University,
St. John's, NL A1B 3X5, Canada
e-mail: fikhan@mun.ca

Mike Paulin

INTECSEA Canada,
WorleyParsons Group,
St. John's, NL A1C 6C9, Canada
e-mail: mike.paulin@intecsea.com

1Corresponding author.

Contributed by the Pressure Vessel and Piping Division of ASME for publication in the JOURNAL OF PRESSURE VESSEL TECHNOLOGY. Manuscript received December 28, 2014; final manuscript received January 13, 2017; published online April 21, 2017. Assoc. Editor: Allen C. Smith.

J. Pressure Vessel Technol 139(4), 041701 (Apr 21, 2017) (8 pages) Paper No: PVT-14-1214; doi: 10.1115/1.4036217 History: Received December 28, 2014; Revised January 13, 2017

When offshore pipelines approach the end of their design life, their condition could threaten oil flow continuity as well as become a potential safety or environmental hazard. Hence, there is a need to assess the remaining life of pipelines to ensure that they can cope with current and future operational demand and integrity challenges. This paper presents a methodology for assessing the condition of aging pipelines and determining the remaining life that can support extended operation without compromising safety and reliability. Applying this methodology would facilitate a well-informed decision that enables decision makers to determine the best strategy for maintaining the integrity of aging pipelines.

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References

Figures

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Fig. 1

Illustration of flaw and its dimension

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Fig. 2

Framework for limit state function evaluation

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Fig. 6

Probability of failure due to burst pressure (ASME)

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Fig. 3

Histogram of the simulated flaw depth

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Fig. 4

Probability of failure due to corrosion

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Fig. 5

Probability of failure due to burst pressure (DNV/BS)

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Fig. 7

Probability of failure due to burst pressure—ASME effective area method

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Fig. 8

Probability of failure—burst and leakage

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Fig. 9

Probability of failure—burst and leakage—linear scale

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Fig. 10

Flow chart outlining the steps for the methodology I & M: inspection & maintenance, LSF: limit state function, MCS: Monte Carlo simulation, Pb: burst pressure, Po: operating pressure, PofT: total probability of failure, PofTarget: target probability of failure, R.V: random variable, Req: requirements, T: time

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