Suction anchors play an important role in the exploration and development of marine natural gas hydrate (NGH). Suction anchors increase the bearing capacity and reduce tilting or sinking risk of underwater wellheads in the exploration and development process. This study proposes a dynamic failure analysis procedure for suction anchor installation based on the DBN-GO method. Firstly, a Goal-Oriented (GO) model is established by analyzing the human and equipment factor nodes in the suction anchor installation operation process. A Bayesian Network (BN) analysis model is set up by mapping the key nodes in the GO model. Then, the Cognitive Reliability and Error Analysis Method (CREAM) and the Dempster–Shafer (D-S) evidence theory are used to quantify the failure probabilities of human and equipment factor nodes in the BN model. The main risk factors are identified using Bayesian backward inference. Finally, the dynamic risk assessment of the suction anchor installation operation is conducted, considering the equipment node transition probability of the BN. Tkae the second production test of natural gas hydrates in the South China Sea as a case study. The study result shows that the failure probability of the suction anchor installation operation is 0.298%, which is at a low-risk level. Suction pump pressure control is the most critical factor leading to human errors. Among the equipment factor, the reliability of the suction pump and the ROV is the most important. Dynamic Bayesian inference shows the risk gradually increases with time. A reasonable maintenance strategy is conducive to reducing the accumulated risks caused by the time-varying degradation of equipment performance. The results could provide significant support in risk management and decision-making for the suction anchor installation operation, which will further promote the environmental sustainability, operational safety and economic feasibility of marine natural gas hydrate development.
Liu et al. (2026) studied this question.