Proceedings of the

The 33rd European Safety and Reliability Conference (ESREL 2023)
3 – 8 September 2023, Southampton, UK

A Methodology for Updating Emergency Schemes by Combining Dynamic Bayesian Networks with Graphical Evaluation and Review Technique

Xuan Liu, Xu An, Xiaojian Yi and Huixing Menga

State Key Laboratory of Explosion Science and Technology, Beijing Institute of Technology, Beijing, China.


The blowout risk in offshore drilling operations is characterized by uncertainty and complexity. Blowout accidents usually result in significant casualties, property losses, and even environmental disasters. To alleviate the consequences of accidents and evaluate the emergency risk, we propose to integrate dynamic Bayesian networks (DBN) and graphical evaluation and review technique (GERT) to develop a risk assessment model. In the proposed methodology, we establish a topological network to describe the failure coupling of nodes in the emergency schemes by DBN. Subsequently, the dynamic failure probability change of different nodes can be obtained through failure probability analysis. To optimize emergency schemes, GERT is integrated into the sensitivity analysis to evaluate the risk of nodes in the emergency schemes. The duration of emergency operations can be optimized by the results. Offshore capping stack, an effective deepwater blowout emergency technique, is used to demonstrate the applicability of the methodology. The results show that the proposed model is beneficial to determine emergency operations in offshore oil and gas activities.

Keywords: Emergency scheme, Dynamic Bayesian network, Graphical evaluation and review technique, Transfer function, Strategy optimization.

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