Real-time risk assessment of explosion on offshore platform using Bayesian network and CFD |
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| Institution: | 1. Centre for Offshore Engineering and Safety Technology, China University of Petroleum, Qingdao, 266580, China;2. Centre for Risk, Integrity and Safety Engineering (C-RISE), Faculty of Engineering and Applied Science, Memorial University of Newfoundland, St. John’s, NL, A1B 3X5, Canada;1. Department of Naval Architecture and Ocean Engineering, College of Engineering, Seoul National University, 1, Gwanak-ro, Gwanak-gu, Seoul 151–744, South Korea;2. Research Institute of Marine Systems Engineering, Department of Naval Architecture and Ocean Engineering, Seoul National University, Seoul, South Korea;1. Centre for Offshore Engineering and Safety Technology, China University of Petroleum, Qingdao 266580, China;2. Centre for Risk, Integrity and Safety Engineering (C-RISE), Faculty of Engineering & Applied Science, Memorial University, St. John''s, NL A1B 3X5, Canada;3. CNOOC Deepwater Development Limited, Guangzhou, 519000, China |
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| Abstract: | Combustion or explosion accident resulting from accidental hydrocarbon release poses a severe threat to the offshore platform's operational safety. Much attention has been paid to the risk of an accident occurring over a long period, while the real-time risk that escalates from a primary accident to a serious one was ignored. In this study, a real-time risk assessment model is presented for risk analysis of release accidents, which may escalate into a combustion or explosion. The proposed model takes advantage of Fault Tree-Event Tree (FT-ET) to describe the accident scenario, and Bayesian network (BN) to obtain the initial probability of each consequence and describe the dependencies among safety barriers. Besides, Computational Fluid Dynamics (CFD) is applied to handle the relationship between gas dispersion and time-dependent risk. Ignition probability model that considering potential ignition sources, gas cloud, and time series are also integrated into this framework to explain the likelihood of accident evolution. A case of release accidents on a production platform is used to test the availability and effectiveness of the proposed methodology, which can be adopted for facilities layout optimization and ignition sources control. |
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| Keywords: | Leak Real-time risk Bayesian network CFD modeling Ignition modeling |
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