Optimal Shale Gas Flowback Water Desalination under Correlated Data Uncertainty

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Title: Optimal Shale Gas Flowback Water Desalination under Correlated Data Uncertainty
Authors: Onishi, Viviani C. | Ruiz-Femenia, Rubén | Salcedo Díaz, Raquel | Carrero-Parreño, Alba | Reyes-Labarta, Juan A. | Caballero, José A.
Research Group/s: Computer Optimization of Chemical Engineering Processes and Technologies (CONCEPT) | Estudios de Transferencia de Materia y Control de Calidad de Aguas (ETMyCCA)
Center, Department or Service: Universidad de Alicante. Instituto Universitario de Ingeniería de los Procesos Químicos | Universidad de Alicante. Departamento de Ingeniería Química
Keywords: Shale Gas | Desalination | Multi effect evaporation | Uncertainty
Knowledge Area: Ingeniería Química
Issue Date: 3-Oct-2017
Publisher: Elsevier
Citation: Computer Aided Chemical Engineering. 2017, 40: 943-948. doi:10.1016/B978-0-444-63965-3.50159-8
Abstract: Optimal flowback water desalination is critical to improve overall efficiency and sustainability of shale gas production. Nonetheless, great uncertainty in well data from shale plays strongly hinders the design task. In this work, we introduce a new stochastic multiscenario optimization model for the robust design of desalination systems under uncertainty. A zero-liquid discharge (ZLD) system composed by multiple-effect evaporation with mechanical vapor recompression (MEE-MVR) is proposed for the desalination of high-salinity shale gas flowback water. Salinity and flowrate of flowback water are both considered as uncertain design parameters, which are described by correlated scenarios with given probability of occurrence. The set of scenarios is generated via Monte Carlo sampling technique from a multivariate normal distribution. ZLD operation is ensured by the design constraint that allows brine concentration near to salt saturation conditions for all scenarios. The stochastic multiscenario nonlinear programming (NLP) model is optimized in GAMS, through the minimization of the expected total annualized cost. Risk analysis based on cumulative probability curves is performed in the uncertain search space, to support decision-makers towards the selection of more robust ZLD desalination systems applied to shale gas flowback water.
Description: Presentation at the 27th European Symposium on Computer-Aided Process Engineering (ESCAPE-27), Barcelona, 2017, 1-5 October.
Sponsor: This project has received funding from the European Union's Horizon 2020 research and innovation program under grand agreement No 640979.
URI: http://hdl.handle.net/10045/80953
ISBN: 978-0-444-64078-9
ISSN: 1570-7946
DOI: 10.1016/B978-0-444-63965-3.50159-8
Language: eng
Type: info:eu-repo/semantics/conferenceObject
Rights: © The authors
Peer Review: si
Publisher version: https://doi.org/10.1016/B978-0-444-63965-3.50159-8
Appears in Collections:Research funded by the EU
INV - ETMyCCA - Comunicaciones a Congresos, Conferencias, etc.
INV - CONCEPT - Comunicaciones a Congresos, Conferencias, etc.

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