Optimization Models for Investment, Operation and Water Management in Shale Gas Supply Chains

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1437668 - GrossmannThe production of shale gas is one of the most important developments that has taken place in the US in the last decade. It has radically changed the availability of energy sources, as well as greatly improved the international competitiveness of the U.S. petrochemical industry from low-cost feedstocks. The Energy Information Administration predicts U.S. shale gas production to grow from 23% to almost 50% of the total gas production for the next 25 years. In order to support this projection, the objective of this proposal is to contribute to the optimal and sustainable development of the shale gas industry through new computational tools for optimizing the investment and operation of production fields and processing plants, as well as optimizing water management and reuse. The proposed computational tools will be based on novel optimization models and advanced mixed-integer programming methods that optimize the design and operation of the supply chain infrastructure, as well as optimizing the use and cost of water management for hydraulic fracturing operations, while accounting for its environmental impact. The motivation for this research is that currently there are virtually no computer tools available to support decision-makers in the development of shale gas facilities. The project will be complemented by educational materials that can be used in undergraduate design courses in chemical engineering. The goal is to make students aware of the engineering challenges and opportunities involved in shale gas production.Intellectual Merit :The primary goal of the proposed work is to develop a new mixed-integer optimization model for the design of shale gas supply chain infrastructures. The proposed model is aimed at optimizing the selection of the number of wells to drill on new/existing pads, size and location of new gas processing plants, location and length of new pipelines for gathering raw gas, delivering dry gas, and natural gas liquids, location and power of gas compressors to be installed, and planning of freshwater consumption from available reservoirs for well drilling and fracturing. The goal of this model is to maximize the net present value of the supply chain infrastructure over a long planning time horizon. A major challenge in the model involves solving a large-scale mixed-integer nonlinear program (MINLP) to global optimality. The proposed project will also involve the development of a detailed operational mixed-integer linear model to optimize water use life cycle for well pads with the objective of reducing freshwater consumption by reuse and recycle, while minimizing transportation and treatment costs. The supply chain and water management models will be extended to minimize environmental impact within a multi-objective optimization framework that incorporates Life Cycle Analysis.Broader Impacts :From a theoretical point of view this research will open new application areas for modeling and optimization that have not been addressed before in process systems engineering. These are likely to impact the academic community by promoting research in the development of new complex MINLP models for design and operation of shale gas processing. From a practical point of view, the proposed project will provide new advanced computer tools that have not been used by shale gas producers, whether large or small. The proposed work on supply chain infrastructure will help to optimally integrate investment and operational decisions, including scheduling the drilling of wells. Furthermore, it is hoped that this work on water management will promote the efficient and sustainable use of water, as well as reducing congestion of roads for its transportation. The proposed models will help to quantitatively assess the environmental impact of shale gas production. From an educational perspective, the PI will engage undergraduates in research in these areas, and develop educational materials in the form of case studies that can be used in the teaching of undergraduate design courses in chemical engineering to make students aware of the challenges and opportunities involved in producing shale gas. Finally, the PI will leverage the project with his industrial partners of the Center for Advanced Process Decision-making, gas producers in the greater Pittsburgh area, and international collaborations with researchers in Argentina and Norway where the production of shale gas is actively pursued. The practical relevance of the proposed models will be validated with case studies provided by industrial collaborators.