Real-time risk assessment of explosion on offshore platform using Bayesian network and CFD

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.