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A Bayesian Belief Network Model for the Risk Assessment and Management of Premature Screen-Out during Hydraulic Fracturing

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  • Zio, Enrico
  • Mustafayeva, Maryam
  • Montanaro, Andrea

Abstract

Hydraulic fracturing is a well completion technique for Oil and Gas production enhancement in both conventional and unconventional reservoirs. However, it can result in the unfavorable consequence of the premature screen-out, which occurs due to the proppant bridging across the perforations or similar restricted flow areas.

Suggested Citation

  • Zio, Enrico & Mustafayeva, Maryam & Montanaro, Andrea, 2022. "A Bayesian Belief Network Model for the Risk Assessment and Management of Premature Screen-Out during Hydraulic Fracturing," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    • Handle: RePEc:eee:reensy:v:218:y:2022:i:pa:s0951832021005913
    DOI: 10.1016/j.ress.2021.108094
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    References listed on IDEAS

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    1. Tosoni, E. & Salo, A. & Govaerts, J. & Zio, E., 2019. "Comprehensiveness of scenarios in the safety assessment of nuclear waste repositories," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 561-573.
    2. Song, Guozheng & Khan, Faisal & Wang, Hangzhou & Leighton, Shelly & Yuan, Zhi & Liu, Hanwen, 2016. "Dynamic occupational risk model for offshore operations in harsh environments," Reliability Engineering and System Safety, Elsevier, vol. 150(C), pages 58-64.
    3. Leimeister, Mareike & Kolios, Athanasios, 2018. "A review of reliability-based methods for risk analysis and their application in the offshore wind industry," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 1065-1076.
    4. Fam, Mei Ling & He, Xuhong & Konovessis, Dimitrios & Ong, Lin Seng, 2020. "Using Dynamic Bayesian Belief Network for analysing well decommissioning failures and long-term monitoring of decommissioned wells," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
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    Cited by:

    1. Liang, Zhenglin & Jiang, Chen & Sun, Muxia & Xue, Zongqi & Li, Yan-Fu, 2023. "Resilience analysis for confronting the spreading risk of contagious diseases," Reliability Engineering and System Safety, Elsevier, vol. 239(C).
    2. Ballester-Ripoll, Rafael & Leonelli, Manuele, 2022. "Computing Sobol indices in probabilistic graphical models," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    3. Hunte, Joshua L. & Neil, Martin & Fenton, Norman E., 2024. "A hybrid Bayesian network for medical device risk assessment and management," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    4. Tao, Longlong & Chen, Liwei & Ge, Daochuan & Yao, Yuantao & Ruan, Fang & Wu, Jie & Yu, Jie, 2022. "An integrated probabilistic risk assessment methodology for maritime transportation of spent nuclear fuel based on event tree and hydrodynamic model," Reliability Engineering and System Safety, Elsevier, vol. 227(C).

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