Optimal Pretreatment System of Flowback Water from Shale Gas Production

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10045/65571
Información del item - Informació de l'item - Item information
Título: Optimal Pretreatment System of Flowback Water from Shale Gas Production
Autor/es: Carrero-Parreño, Alba | Onishi, Viviani C. | Salcedo Díaz, Raquel | Ruiz-Femenia, Rubén | Fraga, Eric S. | Caballero, José A. | Labarta, Juan A.
Grupo/s de investigación o GITE: Computer Optimization of Chemical Engineering Processes and Technologies (CONCEPT)
Centro, Departamento o Servicio: Universidad de Alicante. Departamento de Ingeniería Química | Universidad de Alicante. Instituto Universitario de Ingeniería de los Procesos Químicos
Palabras clave: Shale gas production | Flowback water | Water pretreatment systems | Optimization model | Simultaneous synthesis
Área/s de conocimiento: Ingeniería Química
Fecha de publicación: 22-mar-2017
Editor: American Chemical Society
Cita bibliográfica: Industrial & Engineering Chemistry Research. 2017, 56(15): 4386-4398. doi:10.1021/acs.iecr.6b04016
Resumen: Shale gas has emerged as a potential resource to transform the global energy market. Nevertheless, gas extraction from tight shale formations is only possible after horizontal drilling and hydraulic fracturing, which generally demand large amounts of water. Part of the ejected fracturing fluid returns to the surface as flowback water, containing a variety of pollutants. For this reason, water reuse and water recycling technologies have received further interest for enhancing overall shale gas process efficiency and sustainability. Water pretreatment systems (WPSs) can play an important role for achieving this goal. This paper introduces a new optimization model for WPS simultaneous synthesis, especially developed for flowback water from shale gas production. A multistage superstructure is proposed for the optimal WPS design, including several water pretreatment alternatives. The mathematical model is formulated via generalized disjunctive programming (GDP) and solved by re-formulation as a mixed-integer nonlinear programming (MINLP) problem, to minimize the total annualized cost. Hence, the superstructure allows identifying the optimal pretreatment sequence with minimum cost, according to inlet water composition and wastewater-desired destination (i.e., water reuse as fracking fluid or recycling). Three case studies are performed to illustrate the applicability of the proposed approach under specific composition constraints. Thus, four distinct flowback water compositions are evaluated for the different target conditions. The results highlight the ability of the developed model for the cost-effective WPS synthesis, by reaching the required water compositions for each specified destination.
Patrocinador/es: This project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No. 640979.
URI: http://hdl.handle.net/10045/65571
ISSN: 0888-5885 (Print) | 1520-5045 (Online)
DOI: 10.1021/acs.iecr.6b04016
Idioma: eng
Tipo: info:eu-repo/semantics/article
Derechos: This is an open access article published under an ACS AuthorChoice License, which permits copying and redistribution of the article or any adaptations for non-commercial purposes.
Revisión científica: si
Versión del editor: http://dx.doi.org/10.1021/acs.iecr.6b04016
Aparece en las colecciones:Investigaciones financiadas por la UE
INV - CONCEPT - Artículos de Revistas

Archivos en este ítem:
Archivos en este ítem:
Archivo Descripción TamañoFormato 
Thumbnail2017_Carrero_etal_IndEngChemRes.pdf1,25 MBAdobe PDFAbrir Vista previa


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