A Bayesian Belief Network Model for the Risk Assessment and Management of Premature Screen-Out during Hydraulic Fracturing - Mines Paris Accéder directement au contenu
Article Dans Une Revue Reliability Engineering and System Safety Année : 2022

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

Résumé

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.The objective of this work is to propose a novel framework of analysis that enables to quantify the risk of screen-out occurrence, to identify the riskiest scenarios and to determine the best risk mitigation strategies. The premature screen-out problem is addressed within a Risk Management and Control Process, wherein the qualitative and quantitative assessments of the early screen-out risk are performed by a Features, Events and Processes Analysis structured with a Bayesian Belief Network. The BBN probabilities are subject to a thorough uncertainty and sensitivity analysis. Sensitivity analysis is performed by the Sobol's variance decomposition method and the identified most influential probabilities of the BBN are re-estimated in order to reduce the output uncertainty.Finally, risk mitigation plans are formulated using risk importance measures to identify the riskiest scenarios and cost-benefit analysis to determine the optimal risk reduction actionsThe developed framework has been applied to a case study of vertical wells.
Fichier principal
Vignette du fichier
S0951832021005913.pdf (1.98 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-03907659 , version 1 (05-01-2024)

Licence

Paternité - Pas d'utilisation commerciale

Identifiants

Citer

Enrico Zio, Maryam Mustafayeva, Andrea Montanaro. A Bayesian Belief Network Model for the Risk Assessment and Management of Premature Screen-Out during Hydraulic Fracturing. Reliability Engineering and System Safety, 2022, 218, pp.108094. ⟨10.1016/j.ress.2021.108094⟩. ⟨hal-03907659⟩
25 Consultations
2 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More