12 research outputs found
Environmental and Economic Water Management in Shale Gas Extraction
This paper introduces a comprehensive study of the Life Cycle Impact Assessment (LCIA) of water management in shale gas exploitation. First, we present a comprehensive study of wastewater treatment in the shale gas extraction, including the most common technologies for the pretreatment and three different desalination technologies of recent interest: Single and Multiple-Effect Evaporation with Mechanical Vapor Recompression and Membrane Distillation. The analysis has been carried out through a generic Life Cycle Assessment (LCA) and the ReCiPe metric (at midpoint and endpoint levels), considering a wide range of environmental impacts. The results show that among these technologies Multiple-Effect Evaporation with Mechanical Vapor Recompression (MEE-MVR) is the most suitable technology for the wastewater treatment in shale gas extraction, taking into account its reduced environmental impact, the high water recovery compared to other alternatives as well as the lower cost of this technology. We also use a comprehensive water management model that includes previous results that takes the form of a new Mixed-Integer Linear Programming (MILP) bi-criterion optimization model to address the profit maximization and the minimization Life Cycle Impact Assessment (LCIA), based on its results we discuss the main tradeoffs between optimal operation from the economic and environmental points of view.This project has received funding from the Spanish «Ministerio de EconomĂa, Industria y Competitividad» under the projects CTQ2016-77968-C3-1-P and CTQ2016-77968-C3-2-P (FEDER, UE)
Shale Water Desalination: Multistage membrane distillation considering different configurations and heat integration
This work introduces a simultaneous synthesis of membrane distillation systems with heat exchanger networks (HENs) for desalinating shale gas flowback and produce water. The direct contact and vacuum membrane configurations are the best options for desalination. Moreover, multistage membrane distillation systems usually have higher efficiencies than single-stages processes. For this reason, two different mathematical models for synthetizing multistage direct contact membrane distillation (MSDCMD) and multistage vacuum membrane distillation (MSVMD) are developed and optimized to achieve zero liquid discharge (ZLD) conditions. To this aim, brine discharges are considered to be near to the salt saturation conditions. The multi-stage superstructures are implemented in GAMS and optimized by SBB solver. The mathematical model is formulated via generalized disjunctive programming (GDP) and mixed-integer nonlinear programming (MINLP), to minimize the total annualized cost.This project has received funding from the European Unionâs Horizon 2020 Research and Innovation Programme under grant agreement No. 640979
Optimal Shale Gas Flowback Water Desalination under Correlated Data Uncertainty
Presentation at the 27th European Symposium on Computer-Aided Process Engineering (ESCAPE-27), Barcelona, 2017, 1-5 October.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.This project has received funding from the European Union's Horizon 2020 research and innovation program under grand agreement No 640979
Economic and environmental strategic water management in the shale gas industry: Application of cooperative game theory
In this work, a mixedâinteger linear programming (MILP) model is developed to address optimal shale gasâwater management strategies among shale gas companies that operate relatively close. The objective is to compute a distribution of waterârelated costs and profit among shale companies to achieve a stable agreement on cooperation among them that allows increasing total benefits and reducing total costs and environmental impacts. We apply different solution methods based on cooperative game theory: The Core, the Dual Core, the Shapley value, and the minmax Core. We solved different case studies including a large problem involving four companies and 207 wells. In this example, individual cost distribution (storage cost, freshwater withdrawal cost, transportation cost, and treatment cost) assigned to each player is included. The results show that companies that adopt cooperation strategies improve their profits and enhance the sustainability of their operations through the increase in recycled water.The authors gratefully acknowledge the financial support by the Ministry of Economy, Industry, and Competitiveness from Spain, under the projects CTQ2016-77968-C3-1-P and CTQ2016-77968-C3-2-P (AEI/FEDER, UE)
Holistic Planning Model for Sustainable Water Management in the Shale Gas Industry
To address water planning decisions in shale gas operations, we present a novel water management optimization model that explicitly takes into account the effect of high concentrations of total dissolved solids (TDS) and temporal variations in the impaired water. The model comprises different water management strategies: (a) direct wastewater reuse, which is possible because of new additives tolerant to high TDS concentrations but at the expense of increasing the costs; (b) wastewater treatment, separately taking into account pretreatment, softening, and desalination technologies; and (c) the use of Class II disposal sites. The objective is to maximize the âsustainability profitâ by determining the flowback destination (reuse, degree of treatment, or disposal), the fracturing schedule, the fracturing-fluid composition, and the number of water-storage tanks needed for each period of time. Because of the rigorous determination of TDS in all water streams, the model is a nonconvex MINLP model that is tackled in two steps: first, an MILP model is solved on the basis of McCormick relaxations; next, the binary variables that determine the fracturing schedule are fixed, and a smaller MINLP is solved. Finally, several case studies based on Marcellus Shale Play are optimized to illustrate the effectiveness of the proposed formulation. The model identifies direct reuse as the best water-management option to improve both economic and environmental criteria.This project has received funding from the European Unionâs Horizon 2020 Research and Innovation Program under grant agreement no. 640979 and from the Spanish Ministerio de EconomiaÌ , Industria y Competitividad CTQ2016-77968-C3-02-P (FEDER, UE)
Optimal Pretreatment System of Flowback Water from Shale Gas Production
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
Modeling and optimization of shale gas water management systems
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. Thus, water reuse and water recycling technologies have received further interest for enhancing overall shale gas process efficiency and sustainability. Thereby, the objectives of this thesis are: - Develop mathematical models to treat flowback and produced water at various salinities and flow rates, decreasing the high environmental impact due to the freshwater withdrawal and wastewater generated during shale gas production at minimum cost. - Develop mathematical programming models for planning shale gas water management through the first stage of the well's life to promote the reuse of flowback water by optimizing simultaneously all operations belonging several wellpads. Within the first objective, we developed medium size generalized disjunctive-programming (GDP) models reformulated as mixed integer non-linear programming problems (MINLPs). First, we focused on flowback water pretreatment and later, in wastewater desalination treatment. Particularly, an emergent desalination technology, Membrane Distillation, has been studied. All mathematical models have been implemented using GAMSÂź software. First, we introduce a new optimization model for wastewater from shale gas production including a superstructure with several water pretreatment alternatives. The mathematical model is formulated via GDP to minimize the total annualized cost. Hence, the superstructure developed 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 desalination in thermal or membrane techonologies). As each destination requires specific composition constraints, three case studies illustrate the applicability of the proposed approach. Additionally, 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 water pretreatment system synthesis, by reaching the required water compositions for each specified destination. Regarding desalination technologies, a rigorous optimization model with energy recovery for the synthesis of multistage direct contact membrane distillation (DCMD) system has been developed. The mathematical model is focused on maximizing the total amount of water recovered. The outflow brine is fixed close to salt saturation conditions (300 g·kg-1) approaching zero liquid discharge (ZLD). A sensitivity analysis is performed to evaluate the systemâs behavior under different uncertainty sources such as the heat source availability and inlet salinity conditions. The results emphasize the applicability of this promising technology, especially with low steam cost or waste heat, and reveal variable costs and system configurations depending on inlet conditions. Within the second objective, large-scale multi-period water management problems, and collaborative water management models have been studied. Thus, to address water planning decisions in shale gas operations, in a first stage a new non-convex MINLP optimization model is presented that explicitly takes into account the effect of high concentration of total dissolved solids (TDS) and its temporal variations in the impaired water. The model comprises different water management strategies: direct reuse, treatment or send to Class II disposal wells. The objective is to maximize the âsustainability profitâ to find a compromise solution among the three pillars of sustainability: economic, environmental and social criteria. The solution determines freshwater consumption, flowback destination, the fracturing schedule, fracturing fluid composition and the number of tanks leased at each time period. Because of the rigorous determination of TDS in all water streams, the model is a nonconvex MINLP model that is tackled in two steps: first, an MILP model is solved on the basis of McCormick relaxations for the bilinear terms; next, the binary variables that determine the fracturing schedule are fixed, and a smaller MINLP is solved. Finally, several case studies based on Marcellus Shale Play are optimized to illustrate the effectiveness of the proposed formulation. Later, a simplified version of the shale gas water management model developed in the previous work has been used to study possible cooperative strategies among companies. This model allows increasing benefits and reduces costs and environmental impacts of water management in shale gas production. If different companies are working in the same shale zone and their shale pads are relatively close (under 50 km), they might adopt a cooperative strategy, which can offer economic and environmental advantages. The objective is to compute a distribution of whatever quantifiable unit among the stakeholders to achieve a stable agreement on cooperation among them. To allocate the cost, profit and/or environmental impact among stakeholders, the Core and Shapley value are applied. Finally, the impact of cooperation among companies is shown by two examples involving three and eight players, respectively. The results show that adopting cooperative strategies in shale water management, companies are allowed to improve their benefits and to enhance the sustainability of their operations. The results obtained in this thesis should help to make cost-effective and environmentally-friendly water management decisions in the eventual development of shale gas wells
Modeling and optimization of shale gas water management systems
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. Thus, water reuse and water recycling technologies have received further interest for enhancing overall shale gas process efficiency and sustainability. Thereby, the objectives of this thesis are: - Develop mathematical models to treat flowback and produced water at various salinities and flow rates, decreasing the high environmental impact due to the freshwater withdrawal and wastewater generated during shale gas production at minimum cost. - Develop mathematical programming models for planning shale gas water management through the first stage of the well's life to promote the reuse of flowback water by optimizing simultaneously all operations belonging several wellpads. Within the first objective, we developed medium size generalized disjunctive-programming (GDP) models reformulated as mixed integer non-linear programming problems (MINLPs). First, we focused on flowback water pretreatment and later, in wastewater desalination treatment. Particularly, an emergent desalination technology, Membrane Distillation, has been studied. All mathematical models have been implemented using GAMSÂź software. First, we introduce a new optimization model for wastewater from shale gas production including a superstructure with several water pretreatment alternatives. The mathematical model is formulated via GDP to minimize the total annualized cost. Hence, the superstructure developed 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 desalination in thermal or membrane techonologies). As each destination requires specific composition constraints, three case studies illustrate the applicability of the proposed approach. Additionally, 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 water pretreatment system synthesis, by reaching the required water compositions for each specified destination. Regarding desalination technologies, a rigorous optimization model with energy recovery for the synthesis of multistage direct contact membrane distillation (DCMD) system has been developed. The mathematical model is focused on maximizing the total amount of water recovered. The outflow brine is fixed close to salt saturation conditions (300 g·kg-1) approaching zero liquid discharge (ZLD). A sensitivity analysis is performed to evaluate the systemâs behavior under different uncertainty sources such as the heat source availability and inlet salinity conditions. The results emphasize the applicability of this promising technology, especially with low steam cost or waste heat, and reveal variable costs and system configurations depending on inlet conditions. Within the second objective, large-scale multi-period water management problems, and collaborative water management models have been studied. Thus, to address water planning decisions in shale gas operations, in a first stage a new non-convex MINLP optimization model is presented that explicitly takes into account the effect of high concentration of total dissolved solids (TDS) and its temporal variations in the impaired water. The model comprises different water management strategies: direct reuse, treatment or send to Class II disposal wells. The objective is to maximize the âsustainability profitâ to find a compromise solution among the three pillars of sustainability: economic, environmental and social criteria. The solution determines freshwater consumption, flowback destination, the fracturing schedule, fracturing fluid composition and the number of tanks leased at each time period. Because of the rigorous determination of TDS in all water streams, the model is a nonconvex MINLP model that is tackled in two steps: first, an MILP model is solved on the basis of McCormick relaxations for the bilinear terms; next, the binary variables that determine the fracturing schedule are fixed, and a smaller MINLP is solved. Finally, several case studies based on Marcellus Shale Play are optimized to illustrate the effectiveness of the proposed formulation. Later, a simplified version of the shale gas water management model developed in the previous work has been used to study possible cooperative strategies among companies. This model allows increasing benefits and reduces costs and environmental impacts of water management in shale gas production. If different companies are working in the same shale zone and their shale pads are relatively close (under 50 km), they might adopt a cooperative strategy, which can offer economic and environmental advantages. The objective is to compute a distribution of whatever quantifiable unit among the stakeholders to achieve a stable agreement on cooperation among them. To allocate the cost, profit and/or environmental impact among stakeholders, the Core and Shapley value are applied. Finally, the impact of cooperation among companies is shown by two examples involving three and eight players, respectively. The results show that adopting cooperative strategies in shale water management, companies are allowed to improve their benefits and to enhance the sustainability of their operations. The results obtained in this thesis should help to make cost-effective and environmentally-friendly water management decisions in the eventual development of shale gas wells
Combining Forward and Reverse Osmosis for shale gas wastewater treatment to minimize cost and freshwater consumption
27th European Symposium on Computer Aided Process Engineering (ESCAPE 27), Barcelona, 1st-5th October, 2017.Shale gas production requires significant water demand for well exploitation and a great volume of wastewater is generated since nearly 70 % of the drilling water returns to the surface [1], as flowback water (FBW) and produced water (PW), with different salinities. Their treatment has a double benefit: treated water can replace freshwater (FW) and besides waste volumes are reduced. Conventional desalination technologies can be appropriate for FBW but not for the hypersaline PW. Forward Osmosis (FO) is a promising alternative to deal with PW which can be used as a standalone desalination process or as an advanced pretreatment for other technologies [2]. In this work, we propose a superstructure that combines FO with Reverse Osmosis (RO). Its objective is twofold: to minimize FW consumption in well exploitation as well as the volume of final waste. The superstructure comprises a RO unit; two FO units; and mixers and splitters allowing connections between the units. In the figure, the FO1 and FO2 units act as pretreatments for the RO and as waste concentrators aiming for zero liquid discharge (ZLD). In the F01 unit, FBW is diluted and the sludge from the previous pretreatment (where other contaminants apart from Total Dissolved Solids (TDS) are removed) becomes concentrated. In the FO2 unit, the PW is diluted and the brine from the RO unit becomes concentrated. We formulated a bi-objective NonLinear Programming (NLP) problem that aims simultaneously to minimize the specific total cost ($/m3 drilling water) and the FW consumption (m3). The proposed approach is applied to a case study that uses 8500 m3/day of drilling water. The solution shows the trade-off between the cost and FW consumption and highlights the potential of FO to offer a solution for the treatment of the hypersaline PW and simultaneously reduce the shale gas waste volume.European Unionâs Horizon 2020 Research and Innovation Programme under grant agreement No. 640979
Multi-Objective Optimization of Renewable Energy-Driven Desalination Systems
27th European Symposium on Computer Aided Process Engineering (ESCAPE 27), Barcelona, 1st-5th October, 2017.Environmental impacts related to increasing greenhouse gas emissions and depletion of fossil-fuel reserves and water resources are major global concerns. In this work, we introduce a new multi-objective optimization model for simultaneous synthesis of zero-emission desalination plants driven by renewable energy. The system is particularly developed for zero-liquid discharge (ZLD) desalination of high-salinity shale gas wastewater, aiming to enhance economic and environmental system performance. The mathematical model is based on a multistage superstructure, which integrates a solar assisted Rankine cycle to a multiple-effect evaporation with mechanical vapor recompression (MEE-MVR) plant. For achieving the goal of more sustainable ZLD process, we specify the discharge brine salinity near to salt saturation conditions. The model is formulated as a multi-objective multiperiod non-linear programming (NLP) problem. The model is implemented in GAMS and solved via epsilon-constraint method, through the minimization of total annualized cost and environmental impacts. The economic objective function accounts for capital cost of investment and operational expenses, while environmental criteria are quantified by the life cycle assessment (LCA)-based ReCiPe methodology. A case study is performed to demonstrate the capabilities of the developed model. The obtained set of trade-off Pareto-optimal solutions reveals that integration of renewable energy generation to ZLD desalination plants can lead to significant cost and environmental savings for shale gas industry.European Unionâs Horizon 2020 Research and Innovation Programme under grant agreement No. 640979