Quantitative risk assessment methodology of installation process for deepwater oil and gas equipment

Proper installation of deepwater oil and gas equipment is a prerequisite to ensure its service life. Deepwater equipment faces many challenges during installation, such as the complexity of the installation process and uncertainty of the environment. Thus, risk assessment is necessary to guide personnel in avoiding and addressing potential problems during the installation of deepwater equipment. This study proposes a quantitative risk assessment method of installation process for deepwater oil and gas equipment based on fuzzy Bayesian networks (FBNs). First, the flow chart of deepwater oil and gas equipment in installation process is translated into a main Bayesian networks (BNs). Second, risk factors in different stages of installation are determined from human, management, equipment, environment and third-party interference, and entire risk assessment model is established. Finally, the FBN model is quantitatively analyzed by introducing fuzzy set theory. An empirical study on the installation process of subsea blowout preventer (BOP) is conducted. The results show that the failure of the subsea BOP installation is a small probability event, and equipment factors have the most prominent effect on the installation process. The sensitivity analysis results are consistent with the quantitative analysis. The corresponding improvement measures are proposed according to the analysis results.