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Using stakeholders’ judgement and fuzzy logic theory to analyze the risk influencing factors in oil and gas pipeline projects: Case study in Iraq, Stage II

Kraidi, L, Shah, RK, Matipa, WM and Borthwick, F (2020) Using stakeholders’ judgement and fuzzy logic theory to analyze the risk influencing factors in oil and gas pipeline projects: Case study in Iraq, Stage II. International Journal of Critical Infrastructure Protection, 28. ISSN 1874-5482

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Abstract

Oil and gas pipelines are safe and economic to petroleum products transportation. Nevertheless, enormous risk influencing factors are threatening the safety of these pipelines during the planning, construction and operations stages of these projects. Risk analysis in these projects is hindered by the inaccurate data about the probability and severity levels of the risk influencing factors. This problem is exacerbated further in troubled and developing countries, where the documentations and records are not at the best conditions. This study aims to identify and analyze potential risk influencing factors using a more integrated risk analysis framework. In this a such framework, the critical risk influencing factors and some of applied risk mitigation methods were identified based on a comprehensive review of pipelines projects worldwide. The impact of the identified factors and the effectiveness of mitigation methods were evaluated based on an industry-wide questionnaire survey, which was conducted in Iraq. A Computer-Based Risk Analysis Model (CBRAM) was designed to analyze the risk influencing factors using a fuzzy logic theory to consider any uncertainty that is associated with stakeholders’ judgments and data scarcity. The CBRAM has confirmed the most critical risk influencing factors, which this study has explained the effective methods to manage them.

Item Type: Article
Uncontrolled Keywords: 0802 Computation Theory and Mathematics, 0905 Civil Engineering
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Civil Engineering (merged with Built Env 10 Aug 20)
Publisher: Elsevier
Date Deposited: 06 Aug 2020 08:12
Last Modified: 04 Sep 2021 07:44
DOI or ID number: 10.1016/j.ijcip.2020.100337
URI: https://researchonline.ljmu.ac.uk/id/eprint/12450
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