Leak detection systems (LDSs) play a major role in enhancing reliability and operability of oil and gas pipelines. They have the functional capabilities to detect, locate, and quantify leaks before they can cause devastating effects to the environment and operation. The performance of LDSs is typically influenced by three different types of failures that may have severe consequences: delayed detection, missed detection, and false detection of a leak. The consequences of these failures lead to extensive financial losses. For example, missed detection leads to oil spills and exposes operating companies to financial risk and destroyed image while false detection results in unnecessary deployment of personnel and equipment. To maintain safety of personnel and the environment and ensure operation continuity, LDSs should be assessed regularly. To fulfill this need, a probabilistic performance assessment scheme based on limit state approach for fiber optic LDS has been developed. The inherent uncertainties associated with leak detection and reporting capabilities are modeled to determine the LDS detection failure probability that combines two failure events: missed detection and delayed detection. Moreover, the probability of false detection is derived in terms of the lowest detectable change, the threshold. These three parameters establish the basis for an overall assessment scheme that can be used to predict the performance of the LDS. The proposed assessment scheme has been applied to a case study to demonstrate its usefulness and feasibility.
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April 2016
Research-Article
Probabilistic Performance Assessment of Fiber Optic Leak Detection Systems
Alireda Aljaroudi,
Alireda Aljaroudi
Mem. ASME
Safety and Risk Engineering Group,
Faculty of Engineering and Applied Science,
Memorial University of Newfoundland,
St. John's, NL A1B 3X5, Canada
e-mail: aaa515@mun.ca
Safety and Risk Engineering Group,
Faculty of Engineering and Applied Science,
Memorial University of Newfoundland,
St. John's, NL A1B 3X5, Canada
e-mail: aaa515@mun.ca
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Faisal Khan,
Faisal Khan
Safety and Risk Engineering Group,
Faculty of Engineering and Applied Science,
Memorial University of Newfoundland,
St. John's, NL A1B 3X5, Canada
e-mail: fikhan@mun.ca
Faculty of Engineering and Applied Science,
Memorial University of Newfoundland,
St. John's, NL A1B 3X5, Canada
e-mail: fikhan@mun.ca
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Ayhan Akinturk,
Ayhan Akinturk
Canada National Research Council,
St. John's, NL A1B 3R5, Canada
e-mail: ayhan.akinturk@nrc-cnrc.gc.ca
St. John's, NL A1B 3R5, Canada
e-mail: ayhan.akinturk@nrc-cnrc.gc.ca
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Mahmoud Haddara
Mahmoud Haddara
Safety and Risk Engineering Group,
Faculty of Engineering and Applied Science,
Memorial University of Newfoundland,
St. John's, NL A1B 3X5, Canada
e-mail: mhaddara@mun.ca
Faculty of Engineering and Applied Science,
Memorial University of Newfoundland,
St. John's, NL A1B 3X5, Canada
e-mail: mhaddara@mun.ca
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Alireda Aljaroudi
Mem. ASME
Safety and Risk Engineering Group,
Faculty of Engineering and Applied Science,
Memorial University of Newfoundland,
St. John's, NL A1B 3X5, Canada
e-mail: aaa515@mun.ca
Safety and Risk Engineering Group,
Faculty of Engineering and Applied Science,
Memorial University of Newfoundland,
St. John's, NL A1B 3X5, Canada
e-mail: aaa515@mun.ca
Faisal Khan
Safety and Risk Engineering Group,
Faculty of Engineering and Applied Science,
Memorial University of Newfoundland,
St. John's, NL A1B 3X5, Canada
e-mail: fikhan@mun.ca
Faculty of Engineering and Applied Science,
Memorial University of Newfoundland,
St. John's, NL A1B 3X5, Canada
e-mail: fikhan@mun.ca
Ayhan Akinturk
Canada National Research Council,
St. John's, NL A1B 3R5, Canada
e-mail: ayhan.akinturk@nrc-cnrc.gc.ca
St. John's, NL A1B 3R5, Canada
e-mail: ayhan.akinturk@nrc-cnrc.gc.ca
Mahmoud Haddara
Safety and Risk Engineering Group,
Faculty of Engineering and Applied Science,
Memorial University of Newfoundland,
St. John's, NL A1B 3X5, Canada
e-mail: mhaddara@mun.ca
Faculty of Engineering and Applied Science,
Memorial University of Newfoundland,
St. John's, NL A1B 3X5, Canada
e-mail: mhaddara@mun.ca
1Corresponding author.
Contributed by the Ocean, Offshore, and Arctic Engineering Division of ASME for publication in the JOURNAL OF OFFSHORE MECHANICS AND ARCTIC ENGINEERING. Manuscript received July 24, 2014; final manuscript received October 30, 2015; published online February 3, 2016. Assoc. Editor: Elzbieta Maria Bitner-Gregersen.
J. Offshore Mech. Arct. Eng. Apr 2016, 138(2): 021401 (7 pages)
Published Online: February 3, 2016
Article history
Received:
July 24, 2014
Revised:
October 30, 2015
Citation
Aljaroudi, A., Khan, F., Akinturk, A., and Haddara, M. (February 3, 2016). "Probabilistic Performance Assessment of Fiber Optic Leak Detection Systems." ASME. J. Offshore Mech. Arct. Eng. April 2016; 138(2): 021401. https://doi.org/10.1115/1.4032488
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