Open AccessIn the search of oil and gas incident causal factors: The Gaussian Fuzzy Analytic Hierarchy Process approach
Author(s) -
Fermi Dwi Wicaksono,
Yusri Arshad
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1072/1/012012
Subject(s) - fuzzy logic , gaussian , hierarchy , process (computing) , computer science , function (biology) , representation (politics) , gaussian process , causal analysis , operations research , data mining , risk analysis (engineering) , econometrics , mathematics , artificial intelligence , business , economics , physics , quantum mechanics , market economy , evolutionary biology , politics , political science , law , biology , operating system
Learning from events is a crucial measure to reduce the number of catastrophic incidents on board the oil and gas industry. It is critical to have a better understanding of the root causes behind the incidents. A better understanding of the incident causal factors can be accomplished by investigating thoroughly previous incident reports and determine the most notable factors in contributing to the incidents. This paper mainly elaborates and analyzes incident reports produced by the International Oil and Gas Producer Association’s (IOGP’s) reports from 2010 until 2018 located in the worldwide operation. The most contributing factors lead to the oil and gas incidents are examined in this paper utilizing Gaussian fuzzy analytic hierarchy process, an improved methodology of fuzzy analytic hierarchy process (FAHP) by embedding Gaussian fuzzy number within the evaluation process. Gaussian fuzzy number is obtained by random simulation corresponding to the Gaussian probability density function. The result of this paper reveals the more accurate and realistic representation of incident causal factors determination. This point of view helps in better explaining oil and gas incidents causal factors, where precaution measures should be directed and efficiently managed.