Abstract
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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
