Risk analysis of offshore pipeline due to third party damages

The third party damage also known as external factor that contributed to pipeline failure was an unexpected event that considered as threats to human safety. In this work, two risk assessment approaches namely qualitative and quantitative were adopted to predict and measure the causes of offshore pi...

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Bibliographic Details
Main Authors: E., Amri, Nurul Sa'aadah, Sulaiman, Qaid Alaw, Fares Ahmed
Format: Conference or Workshop Item
Language:English
Published: IOP Publishing Ltd 2019
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/35892/1/Risk%20analysis%20of%20offshore%20pipeline%20due%20to%20third%20party%20damages.pdf
http://umpir.ump.edu.my/id/eprint/35892/
https://doi.org/10.1088/1757-899X/702/1/012053
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Institution: Universiti Malaysia Pahang Al-Sultan Abdullah
Language: English
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Summary:The third party damage also known as external factor that contributed to pipeline failure was an unexpected event that considered as threats to human safety. In this work, two risk assessment approaches namely qualitative and quantitative were adopted to predict and measure the causes of offshore pipeline failure due to the third party damages. Qualitative analysis involving causal and consequences of an event was developed using Bow-tie (BT) model to determine the contributing parameter of an event. The parameters obtained were then converted to Bayesian Network (BN) for a quantitative approach. Based on the qualitative analysis, the major threats identified in third party damage were categorized into "anchor impact" and "impact" meanwhile the consequences were human safety, marine life ecosystem and economical loss. Statistical data from PARLOC 2012 were utilized for BN model and transformed into conditional probability table (CPTs). the results generated indicate that the major contribution to pipeline damage was "trawling". The utilization of Bow-tie and BN analysis may complement the risk analysis of offshore pipeline due to third party damage for more informed pipeline maintenance decisions.