Sustainable Optimal Strategic Planning for Shale Water Management

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10045/81647
Registro completo de metadatos
Registro completo de metadatos
Campo DCValorIdioma
dc.contributorComputer Optimization of Chemical Engineering Processes and Technologies (CONCEPT)es_ES
dc.contributor.authorCarrero-Parreño, Alba-
dc.contributor.authorRuiz-Femenia, Rubén-
dc.contributor.authorCaballero, José A.-
dc.contributor.authorLabarta, Juan A.-
dc.contributor.authorGrossmann, Ignacio E.-
dc.contributor.otherUniversidad de Alicante. Departamento de Ingeniería Químicaes_ES
dc.contributor.otherUniversidad de Alicante. Instituto Universitario de Ingeniería de los Procesos Químicoses_ES
dc.date.accessioned2018-10-10T07:21:23Z-
dc.date.available2018-10-10T07:21:23Z-
dc.date.created2017-11-13-
dc.date.issued2018-07-04-
dc.identifier.citationComputer Aided Chemical Engineering. 2018, 43: 657-662. doi:10.1016/B978-0-444-64235-6.50117-0es_ES
dc.identifier.isbn978-0-444-64078-9-
dc.identifier.issn1570-7946-
dc.identifier.urihttp://hdl.handle.net/10045/81647-
dc.description.abstractIn this work, we introduce a non-convex MINLP optimization model for water management in shale gas production. The superstructure includes: reuse/recycle in the same or neighboring wellpad, treatment in mobile units or in centralized water treatment (CWT) facility, or transport to Class II disposal wells. We consider four different water qualities: flowback water, impaired water, desalinated water and freshwater. Additionally, water blending ratios are unrestricted and friction reducers expenses are calculated accounting for impaired water contamination. The objective is to optimize the fracturing schedule, the number of tanks needed in each time period, flowback destination (reuse, treated or disposal), and fracturing fluid composition by maximizing the “sustainability profit” (Zore et al., 2017). The problem is tackled in two steps. First, we solve an MILP model based on McCormick relaxations. Second, a smaller MINLP is solved in which some binary variables are fixed. The capabilities of the proposed mathematical model are validated against long-time horizon scenario from historical data of the Marcellus Shale play.es_ES
dc.description.sponsorshipThis project has received funding from the European Union’s Horizon 2020 Research and Innovation Program under grant agreement No. 640979 and from the Spanish «Ministerio de Economía, Industria y Competitividad» CTQ2016-77968-C3-02-P (FEDER, UE).es_ES
dc.languageenges_ES
dc.publisherElsevieres_ES
dc.rights© Elsevieres_ES
dc.subjectShale gases_ES
dc.subjectWater managementes_ES
dc.subjectSustainability profites_ES
dc.subjectOptimizationes_ES
dc.subjectMixed-integer nonlinear programminges_ES
dc.subject.otherIngeniería Químicaes_ES
dc.titleSustainable Optimal Strategic Planning for Shale Water Managementes_ES
dc.typeinfo:eu-repo/semantics/conferenceObjectes_ES
dc.peerreviewedsies_ES
dc.identifier.doi10.1016/B978-0-444-64235-6.50117-0-
dc.relation.publisherversionhttps://doi.org/10.1016/B978-0-444-64235-6.50117-0es_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/640979es_ES
Aparece en las colecciones:INV - CONCEPT - Capítulos de Libros
Investigaciones financiadas por la UE

Archivos en este ítem:
Archivos en este ítem:
Archivo Descripción TamañoFormato 
Thumbnail225_preprint_ESCAPE28_ACarrero_SGWM.pdfPreprint (acceso abierto)981,96 kBAdobe PDFAbrir Vista previa


Todos los documentos en RUA están protegidos por derechos de autor. Algunos derechos reservados.