eprintid: 1754 rev_number: 11 eprint_status: archive userid: 6 dir: disk0/00/00/17/54 datestamp: 2016-09-16 06:05:30 lastmod: 2017-02-08 12:21:36 status_changed: 2016-09-16 06:05:30 type: article metadata_visibility: show creators_name: Khakzad, Nima creators_name: Khakzad, Sina creators_name: Khan, Faisal corp_creators: Safety and Risk Engineering Group (SREG), Faculty of Engineering and Applied ScienceMemorial University of Newfoundland corp_creators: Safety and Risk Engineering Group (SREG), Faculty of Engineering and Applied ScienceMemorial University of Newfoundland corp_creators: Safety and Risk Engineering Group (SREG), Faculty of Engineering and Applied ScienceMemorial University of Newfoundland title: Probabilistic risk assessment of major accidents: application to offshore blowouts in the Gulf of Mexico subjects: SS divisions: SHEER full_text_status: none keywords: Major accident Risk analysis Bayesian analysis Accident precursor data Offshore blowout abstract: Major accidents are low-frequency, high-consequence accidents which are not well supported by conventional statistical methods due to the scarcity of directly relevant data. Modeling and decomposition techniques such as event tree have been proved as robust alternatives as they facilitate incorporation of partially relevant near accident data–accident precursor data—in probability estimation and risk analysis of major accidents. In this study, we developed a methodology based on event tree and hierarchical Bayesian analysis to establish informative distributions for offshore blowouts using data of near accidents, such as kicks, leaks, and failure of blowout preventers collected from a variety of offshore drilling rigs. These informative distributions can be used as predictive tools to estimate relevant failure probabilities in the future. Further, having a set of near accident data of a drilling rig of interest, the informative distributions can be updated to render case-specific posterior distributions which are of great importance in quantitative risk analysis. To cope with uncertainties, we implemented the methodology in a Markov Chain Monte Carlo framework and applied it to risk assessment of offshore blowouts in the Gulf of Mexico. date: 2014-06 date_type: published publication: Natural Hazards volume: 74 number: 3 publisher: Springer Verlag pagerange: 1759-1771 id_number: doi:10.1007/s11069-014-1271-8 issn: 0921-030X official_url: http://doi.org/10.1007/s11069-014-1271-8 access_IS-EPOS: limited owner: Publisher citation: Khakzad, Nima and Khakzad, Sina and Khan, Faisal (2014) Probabilistic risk assessment of major accidents: application to offshore blowouts in the Gulf of Mexico. Natural Hazards, 74 (3). pp. 1759-1771. DOI: https://doi.org/10.1007/s11069-014-1271-8