Risk Assessment of Subsea Oil Pipeline Decommissioning Under Uncertainty

ABSTRACT To address the complex challenges of subsea pipeline decommissioning under uncertain conditions, this article proposes a risk assessment methodology integrating the noisy‐or gate model, Bayesian networks (BNs), and Monte Carlo simulation (MCS). The methodology is applied to the decommissioning of the Hainan 8 subsea pipeline as a case study. Twenty‐three risk factors, including behavioral variability, state dependence, inherent uncertainty, cognitive limitations, and control vulnerability, were determined by noisy‐or gate model to establish BN model, risk level and potential losses were classified on the basis of risk probabilities; and the risk probability was analyzed by MCS. The sensitivity analysis is used to identify the key factors affecting the safety risk of subsea pipeline operation. The results indicate that the primary risk factors for subsea pipeline decommissioning include unstable seabed geology, the standardization of hosting operations, and the failure of dynamic positioning. Relevant scientific recommendations for risk prevention measures are provided.