ZhangLaibin / China university of petroleum; Beijing
武胜男 / 中国石油大学(北京)
冯桓榰 / 中国石油大学(北京)
李滨 / 中国石油大学(北京)
As an important equipment to ensure the safety of deepwater drilling operations, the deepwater shear ram preventer can shear the drill pipe and seal the well in case of emergency. This paper proposes a Bayesian network-based reliability analysis method for deepwater shear ram preventer in automatic shearing process. This method can transform the fault tree model with the failure of the deepwater shear ram preventer as the top event into a Bayesian network model during testing intervals. The time-dependent failure probability of the subsystem is predicted by following exponential distribution. On this basis, the reliability of the deepwater shear ram preventer system is estimated in terms of the influence of various events that cause its failure and parameters. The key factor is identified, which affects the reliability of the system, and the reliability of the system decrease over time if no more testing strategies are involved.