Implementation of quantitative risk and cost-benefit analysis in an aging offshore facility
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作者:
Lazuardi, Khoir
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Univ Indonesia, Fac Engn, Dept Chem Engn, Depok, Indonesia
Univ Indonesia, Fac Engn, Dept Chem Engn, Depok, West Java, IndonesiaUniv Indonesia, Fac Engn, Dept Chem Engn, Depok, Indonesia
Lazuardi, Khoir
[1
,3
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Kumaraningrum, Anggraini Ratih
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Natl Res & Innovat Agcy, Bur Publ Commun Gen Affairs & Secretariat, Surabaya, IndonesiaUniv Indonesia, Fac Engn, Dept Chem Engn, Depok, Indonesia
Kumaraningrum, Anggraini Ratih
[2
]
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机构:
Hermansyah, Heri
[1
,3
]
机构:
[1] Univ Indonesia, Fac Engn, Dept Chem Engn, Depok, Indonesia
[2] Natl Res & Innovat Agcy, Bur Publ Commun Gen Affairs & Secretariat, Surabaya, Indonesia
[3] Univ Indonesia, Fac Engn, Dept Chem Engn, Depok, West Java, Indonesia
Riser shutdown valves (SDVs) are installed to isolate hydrocarbon through a subsea pipeline or to protect platforms and personnel from an unintended release of hydrocarbons. Unfortunately, the volume of gas leaking through the SDV is sometimes beyond the predetermined criteria. Therefore, a quantitative risk assessment is needed by conducting cost-benefit analysis (CBA). This is the methodology of this study. First, we carry out a frequency analysis to calculate the frequency of release from an isolatable section using an estimate of the release frequency, event tree analysis, and escalation from consequence modeling. Second, we study the consequences of modeling. Third, we carry out risk analysis and evaluation. Fourth, we do CBA calculation. Fifth, we consider the other perspectives. The results of this study can predict the possibility of riser SDV leakage in offshore facilities during the aging period and optimize operating and investment costs while maintaining safety to reduce the possibility of fire explosions. It poses a challenge because of the complexity of operational systems involving multiple potential contributors and multiple safety measures. The study results show that the probability of fire prediction at SDV with processing facilities increases from 8.10 x 10-09 to 7.93 x 10-05 for the worst case scenario. Case studies show that application of the CBA model can be used to optimize the allocation of safety investments.