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dc.contributor.authorSales, Leonardo de Pádua Agripa-
dc.contributor.authorPitombeira Neto, Anselmo Ramalho-
dc.contributor.authorPrata, Bruno de Athayde-
dc.date.accessioned2022-07-08T18:40:39Z-
dc.date.available2022-07-08T18:40:39Z-
dc.date.issued2018-
dc.identifier.citationPITOMBEIRA-NETO, A.R. et al. A genetic algorithm integrated with Monte Carlo simulation for the field layout design problem. Revue d'IFP Energies nouvelles, v. 73, p. 1-16, 2018pt_BR
dc.identifier.issn1294-4475-
dc.identifier.urihttp://www.repositorio.ufc.br/handle/riufc/67008-
dc.language.isoenpt_BR
dc.publisherRevue d'IFP Energies nouvellespt_BR
dc.subjectOil and gas productionpt_BR
dc.subjectMonte Carlo simulationpt_BR
dc.subjectGenetic algorithmpt_BR
dc.titleA genetic algorithm integrated with Monte Carlo simulation for the field layout design problempt_BR
dc.typeArtigo de Periódicopt_BR
dc.description.abstract-ptbrOil and gas production is moving deeper and further offshore as energy companies seek new sources, making the field layout design problem even more important. Although many optimization models are presented in the revised literature, they do not properly consider the uncertainties in well deliverability. This paper aims at presenting a Monte Carlo simulation integrated with a genetic algorithm that addresses this stochastic nature of the problem. Based on the results obtained, we conclude that the probabilistic approach brings new important perspectives to the field development engineering.pt_BR
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