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Quantitative risk analysis of offshore drilling operations: A Bayesian approach

journal contribution
posted on 2023-05-18, 03:10 authored by Khakzad, N, Faisal KhanFaisal Khan, Amyotte, P
Blowouts are among the most undesired and feared accidents during drilling operations. The dynamic nature of blowout accidents, resulting from both rapidly changing physical parameters and time-dependent failure of barriers, necessitates techniques capable of considering time dependencies and changes during the lifetime of a well. The present work is aimed at demonstrating the application of bow-tie and Bayesian network methods in conducting quantitative risk analysis of drilling operations. Considering the former method, fault trees and an event tree are developed for potential accident scenarios, and then combined to build a bow-tie model. In the latter method, first, individual Bayesian networks are developed for the accident scenarios and finally, an object-oriented Bayesian network is constructed by connecting these individual networks. The Bayesian network method provides greater value than the bow-tie model since it can consider common cause failures and conditional dependencies along with performing probability updating and sequential learning using accident precursors. © 2013 Elsevier Ltd.

History

Publication title

Safety Science

Volume

57

Pagination

108-117

ISSN

0925-7535

Department/School

Australian Maritime College

Publisher

Elsevier Science Bv

Place of publication

Po Box 211, Amsterdam, Netherlands, 1000 Ae

Repository Status

  • Restricted

Socio-economic Objectives

Environmentally sustainable mineral resource activities not elsewhere classified