Sustainable Optimal Strategic Planning for Shale Water Management

Please use this identifier to cite or link to this item: http://hdl.handle.net/10045/81647
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Title: Sustainable Optimal Strategic Planning for Shale Water Management
Authors: Carrero-Parreño, Alba | Ruiz-Femenia, Rubén | Caballero, José A. | Labarta, Juan A. | Grossmann, Ignacio E.
Research Group/s: Computer Optimization of Chemical Engineering Processes and Technologies (CONCEPT)
Center, Department or Service: Universidad de Alicante. Departamento de Ingeniería Química | Universidad de Alicante. Instituto Universitario de Ingeniería de los Procesos Químicos
Keywords: Shale gas | Water management | Sustainability profit | Optimization | Mixed-integer nonlinear programming
Knowledge Area: Ingeniería Química
Date Created: 13-Nov-2017
Issue Date: 4-Jul-2018
Publisher: Elsevier
Citation: Computer Aided Chemical Engineering. 2018, 43: 657-662. doi:10.1016/B978-0-444-64235-6.50117-0
Abstract: In 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.
Sponsor: This 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).
URI: http://hdl.handle.net/10045/81647
ISBN: 978-0-444-64078-9
ISSN: 1570-7946
DOI: 10.1016/B978-0-444-64235-6.50117-0
Language: eng
Type: info:eu-repo/semantics/conferenceObject
Rights: © Elsevier
Peer Review: si
Publisher version: https://doi.org/10.1016/B978-0-444-64235-6.50117-0
Appears in Collections:INV - CONCEPT - Capítulos de Libros
Research funded by the EU

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