Dynamic risk analysis of emergency operations in deepwater blowout accidents

The risk in emergency operations can amplify accident losses and threaten the safe achievement of response objectives. In this paper, by considering dynamic characteristics operations, we propose an integrated model estimating probability failure integrating fault tree (FT), Bayesian network (DBN), fuzzy set theory. hybrid model, FT is utilized to identify risk-influencing factors operations. DBN applied capture features process. presence limited prior knowledge, theory employed determine probabilities root nodes. methodology evaluate oil recovery deepwater blowout accident. Particularly, assessed lowering, installation cutting equipment, as well formation gas hydrate. their correlations are identified. influence priority order process on operation expounded. Eventually, a DBN-based for developed. captures spatial variability parameters simulates evolution over time space. mutual information conduct sensitivity analysis diagnostic reasoning model.