An optimization framework for the integration of water management and shale gas supply chain design

This study presents the mathematical formulation and implementation of a comprehensive optimization framework for the assessment of shale gas resources. The framework simultaneously integrates water management and the design and planning of the shale gas supply chain, from the shale formation to final product demand centers and from fresh water supply for hydraulic fracturing to water injection and/or disposal. The framework also addresses some issues regarding wastewater quality, i.e., total dissolved solids (TDS) concentration, as well as spatial and temporal variations in gas composition, features that typically arise in exploiting shale formations. In addition, the proposed framework also considers the integration of different modeling, simulation and optimization tools that are commonly used in the energy sector to evaluate the technical and economic viability of new energy sources. Finally, the capabilities of the proposed framework are illustrated through two case studies (A and B) involving 5 well-pads operating with constant and variable gas composition, respectively. The effects of the modeling of variable TDS concentration in the produced wastewater is also addressed in case study B

Integration of Pumping Profile Design and Water Management Optimization for Shale Gas Production Systems

Unconventional shale gas production in the United States has been largely improved due to the development of hydraulic fracturing technology. However, the shale gas production system is generally complex; further, such enhanced levels of production have generated great concerns on its accompanying environmental implications, especially regarding shale gas water management. To handle the complexity associated with shale gas production system and identify the sustainable water management strategy, many optimization-based approaches have been developed. However, few of them considered the hydraulic fracturing operation as a dynamic process, where the pumping profile directly determines the volume of freshwater consumed and affects the production rates of both shale gas and wastewater. Considering the significant spatiotemporal variation in water footprint of hydraulic fracturing, those obtained planning and operational decisions of shale gas production system could be suboptimal and thus need to be updated when well development strategy changes. From another perspective, one problem could be that the pumping profile is generally designed to only maximize well productivity, without considering the impact of water management. To handle these challenges, the overall objective of this research is to develop a framework for the integration of pumping profile design and water management optimization to achieve the economically viable and environmentally sustainable water management strategy along with maximizing shale gas production. To this end, we initially focus on the development of a novel controller design framework for hydraulic fracturing while explicitly taking into account the associated post-fracturing water management. In particular, a dynamic input-output model is developed to estimate the characteristics of shale gas wastewater produced; and, a mapping-based technique is proposed to estimate the total annual cost of wastewater management and total revenue from shale gas. This framework is demonstrated to be capable to balance the trade-offs between hydraulic fracturing and water management by manipulating the pumping profile. Subsequently, we further extend this study by considering the following practical considerations. First, to better understand the significant spatiotemporal variation in water footprint associated with shale gas well development, the real water-use and flowback and produced (FP) water production data for individual shale gas wells drilled in the Eagle Ford and Marcellus shale regions are collected and analyzed. Herein, a typical model of shale gas production system is utilized to demonstrate how the variation in water recovery ratio can affect the optimal design and operation decisions. Second, to better describe the complex shale gas production system, an optimization model for shale gas supply chain network (SGSCN) incorporating of hydraulic fracturing water cycle is developed. Herein, capacity planning for both large-scale conventional facility and small-scale modular device is considered to achieve a flexible and efficient water management strategy. Third, to better integrate the optimization of shale gas production system and control of hydraulic fracturing, an online integrated scheduling and control framework with two feedback loops is proposed. Herein, the offset-free model predictive control (MPC) scheme is designed to compensate for plant-model mismatch

A Comprehensive Techno-Economic Framework for Shale Gas Exploitation and Distribution in the United States

Over the past years, shale gas has turned into one of the most significant sources of energy in the United States. Technological advancements have provided the energy industry with the necessary tools to allow the economic exploitation of an enormous volume of natural gas trapped in shale formations. This has boosted the domestic gas production and generated a boom in other sectors of the economy in the country. However, major challenges are involved in the development of shale gas resources. A drastic decline of wells’ productivity, the costs involved in the gas production and distribution facets, and the volatile behavior of the energy market represent some of the complexities faced by a gas operator. In this context, the utilization of a comprehensive frameworks to analyze and develop long-term strategies can represent a meaningful supporting tool for shale gas operators. The main objective of this research work is the development and implementation a novel techno-economic framework for the optimal exploitation and delivery of shale gas in the United States. The proposed framework is based on an interdisciplinary approach that combines data driven techniques, petroleum engineering practices, reservoir simulations and mathematical programming methods. Data analysis algorithms are implemented to guide the decision-making processes involved in the unconventional reservoir and define the predominant trends of certain exogenous parameters of the system. Petroleum engineering practices and reservoir simulation models are required for a realistic description of the formations and the proper definition of strategies to extract the gas from the shale rock. Finally, the mathematical programming is required for describing the surface facilities design and operations to ensure the allocation of the shale gas in the different commercialization points. The output of this framework will provide the optimal operations and infrastructure by maximizing the net present value (NPV). To demonstrate the efficacy of the proposed decision-making structure, a case study based on the liquid-rich region of the Marcellus play is considered in this work. The application of the proposed framework depicts the influence of reservoir complexities and external factors in establishing optimal strategic decisions for the exploitation, processing and allocation of shale gas. The coordination of the different facets including the drilling and completion activities and the design and operation of the surface facilities has a key role in maintaining the economy of a shale gas venture above its economic threshold

Disclosing water-energy-economics nexus in shale gas development

Shale gas has gained importance in the energy landscape in recent decades. However, its development has raised environmental concerns, especially, those associated with water management. Thus, the assessment of water management aspects, which inevitably impact the economic aspects, is crucial in evaluating the merits of any project exploiting this energy source. This paper provides a review of the economic and environmental implications of shale gas development around the world. Furthermore, to demonstrate the interplay between the various technical, environmental and economic factors in concrete terms, we report on a specific set of case studies conducted using an integrated decision-support tool that has been implemented to model and optimize shale gas development projects. The case study results confirm that the gas breakeven price decreases with expansion in scale of the shale gas development, i.e. increasing the number of well-pads in the system. However, scale also increases the options for water re-use and recycle in drilling and fracturing operations, which can result in lower freshwater withdrawal intensity. Moreover, under water scarcity scenarios, the choice of well-pad designs that are inherently less water intensive was found to be more cost-effective than water re-use or/and recycle strategies at reducing net freshwater demand. Similar trends were observed when the impact of wastewater quality, i.e. total dissolved solids concentration, on the optimal development strategy of shale gas plays was investigated. The results of these case studies reveal that greater efforts are needed at characterizing freshwater availability and wastewater quality for the evaluation of both the economic and environmental aspects of shale gas development

A contribution to support decision making in energy/water sypply chain optimisation

The seeking of process sustainability forces enterprises to change their operations. Additionally, the industrial globalization implies a very dynamic market that, among other issues, promotes the enterprises competition. Therefore, the efficient control and use of their Key Performance Indicators, including profitability, cost reduction, demand satisfaction and environmental impact associated to the development of new products, is a significant challenge. All the above indicators can be efficiently controlled through the Supply Chain Management. Thus, companies work towards the optimization of their individual operations under competitive environments taking advantage of the flexibility provided by the virtually inexistent world market restrictions. This is achieved by the coordination of the resource flows, across all the entities and echelons belonging to the system network. Nevertheless, such coordination is significantly complicated if considering the presence of uncertainty and even more if seeking for a win-win outcome. The purpose of this thesis is extending the current decision making strategies to expedite these tasks in industrial processes. Such a contribution is based on the development of efficient mathematical models that allows coordinating large amount of information synchronizing the production and distribution tasks in terms of economic, environmental and social criteria. This thesis starts presents an overview of the requirements of sustainable production processes, describing and analyzing the current methods and tools used and identifying the most relevant open issues. All the above is always within the framework of Process System Engineering literature. The second part of this thesis is focused in stressing the current Multi-Objective solution strategies. During this part, first explores how the profitability of the Supply Chain can be enhanced by considering simultaneously multiple objectives under demand uncertainties. Particularly, solution frameworks have been proposed in which different multi-criteria decision making strategies have been combined with stochastic approaches. Furthermore, additional performance indicators (including financial and operational ones) have been included in the same solution framework to evaluate its capabilities. This framework was also applied to decentralized supply chains problems in order to explore its capabilities to produce solution that improves the performances of each one of the SC entities simultaneously. Consequently, a new generalized mathematical formulation which integrates many performance indicators in the production process within a supply chain is efficiently solved. Afterwards, the third part of the thesis extends the proposed solution framework to address the uncertainty management. Particularly, the consideration of different types and sources of uncertainty (e.g. external and internal ones) where considered, through the implementation of preventive approaches. This part also explores the use of solution strategies that efficiently selects the number of scenarios that represent the uncertainty conditions. Finally, the importance and effect of each uncertainty source over the process performance is detailed analyzed through the use of surrogate models that promote the sensitivity analysis of those uncertainties. The third part of this thesis is focused on the integration of the above multi-objective and uncertainty approaches for the optimization of a sustainable Supply Chain. Besides the integration of different solution approaches, this part also considers the integration of hierarchical decision levels, by the exploitation of mathematical models that assess the consequences of considering simultaneously design and planning decisions under centralized and decentralized Supply Chains. Finally, the last part of this thesis provides the final conclusions and further work to be developed.La globalización industrial genera un ambiente dinámico en los mercados que, entre otras cosas, promueve la competencia entre corporaciones. Por lo tanto, el uso eficiente de las los indicadores de rendimiento, incluyendo rentabilidad, satisfacción de la demanda y en general el impacto ambiental, representa un area de oportunidad importante. El control de estos indicadores tiene un efecto positivo si se combinan con la gestión de cadena de suministro. Por lo tanto, las compañías buscan definir sus operaciones para permanecer activas dentro de un ambiente competitivo, tomando en cuenta las restricciones en el mercado mundial. Lo anterior puede ser logrado mediante la coordinación de los flujos de recursos a través de todas las entidades y escalones pertenecientes a la red del sistema. Sin embargo, dicha coordinación se complica significativamente si se quiere considerar la presencia de incertidumbre, y aún más, si se busca exclusivamente un ganar-ganar. El propósito de esta tesis es extender el alcance de las estrategias de toma de decisiones con el fin de facilitar estas tareas dentro de procesos industriales. Estas contribuciones se basan en el desarrollo de modelos matemáticos eficientes que permitan coordinar grandes cantidades de información sincronizando las tareas de producción y distribución en términos económicos, ambientales y sociales. Esta tesis inicia presentando una visión global de los requerimientos de un proceso de producción sostenible, describiendo y analizando los métodos y herramientas actuales así como identificando las áreas de oportunidad más relevantes dentro del marco de ingeniería de procesos La segunda parte se enfoca en enfatizar las capacidades de las estrategias de solución multi-objetivo, durante la cual, se explora el mejoramiento de la rentabilidad de la cadena de suministro considerando múltiples objetivos bajo incertidumbres en la demanda. Particularmente, diferentes marcos de solución han sido propuestos en los que varias estrategias de toma de decisión multi-criterio han sido combinadas con aproximaciones estocásticas. Por otra parte, indicadores de rendimiento (incluyendo financiero y operacional) han sido incluidos en el mismo marco de solución para evaluar sus capacidades. Este marco fue aplicado también a problemas de cadenas de suministro descentralizados con el fin de explorar sus capacidades de producir soluciones que mejoran simultáneamente el rendimiento para cada uno de las entidades dentro de la cadena de suministro. Consecuentemente, una nueva formulación que integra varios indicadores de rendimiento en los procesos de producción fue propuesta y validada. La tercera parte de la tesis extiende el marco de solución propuesto para abordar el manejo de incertidumbres. Particularmente, la consideración de diferentes tipos y fuentes de incertidumbre (p.ej. externos e internos) fueron considerados, mediante la implementación de aproximaciones preventivas. Esta parte también explora el uso de estrategias de solución que elige eficientemente el número de escenarios necesario que representan las condiciones inciertas. Finalmente, la importancia y efecto de cada una de las fuentes de incertidumbre sobre el rendimiento del proceso es analizado en detalle mediante el uso de meta modelos que promueven el análisis de sensibilidad de dichas incertidumbres. La tercera parte de esta tesis se enfoca en la integración de las metodologías de multi-objetivo e incertidumbre anteriormente expuestas para la optimización de cadenas de suministro sostenibles. Además de la integración de diferentes métodos. Esta parte también considera la integración de diferentes niveles jerárquicos de decisión, mediante el aprovechamiento de modelos matemáticos que evalúan lasconsecuencias de considerar simultáneamente las decisiones de diseño y planeación de una cadena de suministro centralizada y descentralizada. La parte final de la tesis detalla las conclusiones y el trabajo a futuro necesario sobre esta línea de investigaciónPostprint (published version

Game theoretic optimisation in process and energy systems engineering: A review

Game theory is a framework that has been used by various research fields in order to represent dynamic correlation among stakeholders. Traditionally, research within the process and energy systems engineering community has focused on the development of centralised decision making schemes. In the recent years, decentralised decision-making schemes have attracted increasing attention due to their ability to capture multi-stakeholder dynamics in a more accurate manner. In this article, we survey how centralised and decentralised decision making has been facilitated by game theoretic approaches. We focus on the deployment of such methods in process systems engineering problems and review applications related to supply chain optimisation problems, design and operations, and energy systems optimisation. Finally, we analyse different game structures based on the degree of cooperation and how fairness criteria can be employed to find fair payoff allocations

Sizing Geographic of the Shale Gas Supply Chain: A Case of Mexico

With the enactment of energy reform in Mexico, some of the energy sector activities are opened to national and foreign private investment. It is expected that this new panorama generates important changes for this sector and thus produce significant positive effects on the economy, especially if national companies associated with its supply chain manage to insert in the new productive dynamic. To locate this context, this research allowed identifying, typifying and quantifying Mexican companies dedicated to carrying out economic activities associated with the shale gas core business, in order to measure each of the links in its supply chain and identify some of its main strengths and opportunities. The results show that in Mexico exist mainly micro and small enterprises engaged in the production of goods and services for this sector, supported in conventional resources, with low possibility of effective integration into the supply chain competitively in cost and quality, against international companies with experience in conducting this kind of activities

Modular Supply Network Optimization of Renewable Ammonia and Methanol Co-production

To reduce the use of fossil fuels and other carbonaceous fuels, renewable energy sources such as solar, wind, geothermal energy have been suggested to be promising alternative energy that guarantee sustainable and clean environment. However, the availability of renewable energy has been limited due to its dependence on weather and geographical location. This challenge is intended to be solved by the utilization of the renewable energy in the production of chemical energy carriers. Hydrogen has been proposed as a potential renewable energy carrier, however, its chemical instability and high liquefaction energy makes researchers seek for other alternative energy carriers. Ammonia and methanol can serve as promising alternative energy carriers due to their chemical stability at room temperature, low liquefaction energy, high energy value. The co-production of these high energy dense energy carriers offers economic and environmental advantages since their synthesis involve the direct utilization of CO2 and common unit operations. This problem report aims to review the optimization of the co-production of methanol and ammonia from renewable energy. Form this review, research challenges and opportunities are identified in the following areas: (i) optimization of methanol and ammonia co-production under renewable and demand uncertainty, (ii) impacts of the modular exponent on the feasibility of co-production of ammonia and methanol, and (iii) development of modern computational tools for systems-based analysis

Modeling the natural gas supply chain for sustainable growth policy

Natural gas has been used globally as a transitional fuel for supporting a green-energy-supply strategy, which has been questioned for the intermittence and lack of reliability of renewables. This paper proposes a System Dynamics model for assessing alternative security of supply policy along the natural gas value chain. The model incorporates demand, transport, production and reserves of natural gas variables according to a systemic perspective. It also includes a module for evaluating the effect of natural gas price on the demand and supply levels, respectively. Alternative supply policies are evaluated under different scenarios. The chosen case-study focuses on the Colombian natural gas industry with the purpose of assessing how the impact of public policies affect supply and demand. Particularly, policies consider the allocation of resources along the natural gas supply chain, seeking to promote the development of infrastructure oriented to mitigate the risk of provision shortages

Economic and environmental strategic water management in the shale gas industry: Application of cooperative game theory

In this work, a mixed‐integer linear programming (MILP) model is developed to address optimal shale gas‐water management strategies among shale gas companies that operate relatively close. The objective is to compute a distribution of water‐related 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)