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dc.contributor.author
Drouven, Markus G.  
dc.contributor.author
Grossmann, Ignacio E.  
dc.contributor.author
Cafaro, Diego Carlos  
dc.date.available
2017-07-14T18:01:13Z  
dc.date.issued
2017-06  
dc.identifier.citation
Drouven, Markus G.; Grossmann, Ignacio E.; Cafaro, Diego Carlos; Stochastic programming models for optimal shale well development and refracturing planning under uncertainty; Wiley; Aiche Journal; 6-2017  
dc.identifier.issn
0001-1541  
dc.identifier.uri
http://hdl.handle.net/11336/20626  
dc.description.abstract
In this work we present an optimization framework for shale gas well development and refracturing planning. This problem is concerned with if and when a new shale gas well should be drilled at a prospective location, and whether or not it should be refractured over its lifespan. We account for exogenous gas price uncertainty and endogenous well performance uncertainty. We propose a mixed-integer linear, two-stage stochastic programming model embedded in a moving horizon strategy to dynamically solve the planning problem. A generalized production estimate function is described that predicts the gas production over time depending on how often a well has been refractured, and when exactly it was restimulated last. From a detailed case study, we conclude that early in the life of an active shale well, refracturing makes economic sense even in low-price environments, whereas additional restimulations only appear to be justified if prices are high.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
Wiley  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
Shale Gas  
dc.subject
Refracturing  
dc.subject
Planning  
dc.subject
Stochastic Programming  
dc.subject.classification
Ingeniería de Procesos Químicos  
dc.subject.classification
Ingeniería Química  
dc.subject.classification
INGENIERÍAS Y TECNOLOGÍAS  
dc.title
Stochastic programming models for optimal shale well development and refracturing planning under uncertainty  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2017-07-13T18:46:57Z  
dc.journal.pais
Estados Unidos  
dc.journal.ciudad
Hoboken  
dc.description.fil
Fil: Drouven, Markus G.. University Of Carnegie Mellon. Department Of Chemical Engineering; Estados Unidos  
dc.description.fil
Fil: Grossmann, Ignacio E.. University Of Carnegie Mellon. Department Of Chemical Engineering; Estados Unidos  
dc.description.fil
Fil: Cafaro, Diego Carlos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentina  
dc.journal.title
Aiche Journal  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1002/aic.15804  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/http://onlinelibrary.wiley.com/doi/10.1002/aic.15804/abstract