Fire risk analysis of offshore drilling operations based on Bayesian networks

Offshore oil and gas play a crucial role in meeting the energy demands of modern economies. However, the risks associated with offshore activities, such as fires and explosions, can lead to significant losses. Consequently, risk analysis of offshore operations is imperative. This paper introduces a Bayesian network approach to analyze the risks associated with offshore oil and gas activities. Initially, fuzzy set theory is employed to convert domain knowledge into quantitative prior probabilities. Insigh ts from industry experts and the literature then inform the development of a fault tree tailored to offshore operations. This fault t ree is integrated into a Bayesian network framework, enhancing the analysis of risk evolution mechanisms in detail. Subsequent ly, sensitivity analysis is conducted to identify and propose risk control measures. The applicability of the proposed method is demonstrated through a case study on offshore drilling operations, specifically analyzing fire risk. The results indicate tha t this method holds potential for application across various industrial systems.