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Reliability modeling of subsea SISs partial testing subject to delayed restoration

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  • Wu, Shengnan
  • Zhang, Laibin
  • Zheng, Wenpei
  • Liu, Yiliu
  • Lundteigen, Mary Ann

Abstract

Subsea oil and gas production has always involved the challenging task of determining the overall reliability of safeguarding systems, such as safety instrumented systems (SISs). Partial testing and delayed restoration of SISs are the main issues in operation and maintenance activities. This paper proposes a novel reliability-modeling methodology for subsea SISs subject to partial testing and delayed restoration. The proposed methodology incorporates an increasing failure rate in conjunction with dangerous undetected failures for the final elements. Approximation formulas for evaluating the average probability of failure on demand are derived for SISs in the low-demand operating mode. In addition, the effects of degradation are modeled by following Weibull rules in different subsequent partial testing intervals. In contrast to previous works, the present research accounts for delayed restoration after detecting failures and also considers the repair time for different scenarios. The proposed formulas are compared with the existing ones for partial verification. A case study on the shutdown valves of a subsea high-integrity pressure protection system is presented to illustrate the feasibility of the proposed methodology. It is also proven that the proposed approximation offers a robust opportunity for testing strategy optimization and performance improvement of SISs.

Suggested Citation

  • Wu, Shengnan & Zhang, Laibin & Zheng, Wenpei & Liu, Yiliu & Lundteigen, Mary Ann, 2019. "Reliability modeling of subsea SISs partial testing subject to delayed restoration," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
  • Handle: RePEc:eee:reensy:v:191:y:2019:i:c:s095183201830125x
    DOI: 10.1016/j.ress.2019.106546
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    References listed on IDEAS

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    4. Chuan Wang & Jun Gou & Yingcheng Tian & Hao Jin & Chao Yu & Yupeng Liu & Jiajun Ma & Yong Xia, 2022. "Reliability and availability evaluation of subsea high integrity pressure protection system using stochastic Petri net," Journal of Risk and Reliability, , vol. 236(3), pages 508-521, June.

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