Optimal Pretreatment System of Flowback Water from Shale Gas Production
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http://hdl.handle.net/10045/65571
Título: | Optimal Pretreatment System of Flowback Water from Shale Gas Production |
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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 |
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Archivo | Descripción | Tamaño | Formato | |
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2017_Carrero_etal_IndEngChemRes.pdf | 1,25 MB | Adobe PDF | Abrir Vista previa | |
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