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Reliability analysis of subsea wellhead system subject to fatigue and degradation during service life

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  • Wu, Shengnan
  • Zhang, Qiao
  • Li, Bin
  • Zhang, Laibin
  • Zheng, Wenpei
  • Li, Zhong
  • Li, Zhandong
  • Liu, Yiliu

Abstract

Subsea wellhead systems play a critical role in ensuring the safe exploitation of offshore oil and gas during offshore drilling and production operation stages. However, due to the complexity of the marine environment and operating condition, this kind of structure is prone to the failure caused by cumulative effects of the fatigue and degradation of components. This paper presents a Markov- Monte Carlo-DBN-based approach to comprehensively predict the reliability of subsea wellhead systems and diagnose the underlying root cause during its service life. Multi-factor impacts on system performance are considered for modeling. A multistate transition model of wellhead components is proposed to analyze system degradation. Reliability evaluation of the critical component is performed and verified by employing the Monte Carlo simulation-based method which is also used to address the issue of insufficient data for subsea wellhead fatigue prediction. By embedding multi-factor effects and multistate transition into DBN, the system state can be effectively updated. An example of a subsea wellhead system demonstrates the application of this approach, through which the system reliability during its service life is predicted, and the most important factors that affect the system's reliability and deserve special attention are identified.

Suggested Citation

  • Wu, Shengnan & Zhang, Qiao & Li, Bin & Zhang, Laibin & Zheng, Wenpei & Li, Zhong & Li, Zhandong & Liu, Yiliu, 2023. "Reliability analysis of subsea wellhead system subject to fatigue and degradation during service life," Reliability Engineering and System Safety, Elsevier, vol. 239(C).
    • Handle: RePEc:eee:reensy:v:239:y:2023:i:c:s0951832023004088
    DOI: 10.1016/j.ress.2023.109494
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    Cited by:

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    2. Tao, Haohan & Jia, Peng & Wang, Xiangyu & Wang, Liquan, 2024. "Reliability analysis of subsea control module based on dynamic Bayesian network and digital twin," Reliability Engineering and System Safety, Elsevier, vol. 248(C).

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