Multi-period planning, design, and strategic models for long-term, quality-sensitive shale gas development

In this work we address the long‐term, quality‐sensitive shale gas development problem. This problem involves planning, design, and strategic decisions such as where, when, and how many shale gas wells to drill, where to lay out gathering pipelines, as well as which delivery agreements to arrange. O...

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Veröffentlicht in:	AIChE journal Jg. 62; H. 7; S. 2296 - 2323
Hauptverfasser:	Drouven, Markus G., Grossmann, Ignacio E.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Blackwell Publishing Ltd 01.07.2016 American Institute of Chemical Engineers
Schlagworte:	Chemical engineering Chemical engineers Decisions Design engineering Development strategies Mathematical models mixed-integer programming Natural gas exploration Nonlinear programming Oil shale Petroleum engineering planning scheduling Shale gas Shales Strategy
ISSN:	0001-1541, 1547-5905
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Abstract	In this work we address the long‐term, quality‐sensitive shale gas development problem. This problem involves planning, design, and strategic decisions such as where, when, and how many shale gas wells to drill, where to lay out gathering pipelines, as well as which delivery agreements to arrange. Our objective is to use computational models to identify the most profitable shale gas development strategies. For this purpose we propose a large‐scale, nonconvex, mixed‐integer nonlinear programming model. We rely on generalized disjunctive programming to systematically derive the building blocks of this model. Based on a tailor‐designed solution strategy we identify near‐global solutions to the resulting large‐scale problems. Finally, we apply the proposed modeling framework to two case studies based on real data to quantify the value of optimization models for shale gas development. Our results suggest that the proposed models can increase upstream operators’ profitability by several million U.S. dollars. © 2016 American Institute of Chemical Engineers AIChE J, 62: 2296–2323, 2016
AbstractList	In this work we address the long-term, quality-sensitive shale gas development problem. This problem involves planning, design, and strategic decisions such as where, when, and how many shale gas wells to drill, where to lay out gathering pipelines, as well as which delivery agreements to arrange. Our objective is to use computational models to identify the most profitable shale gas development strategies. For this purpose we propose a large-scale, nonconvex, mixed-integer nonlinear programming model. We rely on generalized disjunctive programming to systematically derive the building blocks of this model. Based on a tailor-designed solution strategy we identify near-global solutions to the resulting large-scale problems. Finally, we apply the proposed modeling framework to two case studies based on real data to quantify the value of optimization models for shale gas development. Our results suggest that the proposed models can increase upstream operators' profitability by several million U.S. dollars. copyright 2016 American Institute of Chemical Engineers AIChE J, 62: 2296-2323, 2016 In this work we address the long‐term, quality‐sensitive shale gas development problem. This problem involves planning, design, and strategic decisions such as where, when, and how many shale gas wells to drill, where to lay out gathering pipelines, as well as which delivery agreements to arrange. Our objective is to use computational models to identify the most profitable shale gas development strategies. For this purpose we propose a large‐scale, nonconvex, mixed‐integer nonlinear programming model. We rely on generalized disjunctive programming to systematically derive the building blocks of this model. Based on a tailor‐designed solution strategy we identify near‐global solutions to the resulting large‐scale problems. Finally, we apply the proposed modeling framework to two case studies based on real data to quantify the value of optimization models for shale gas development. Our results suggest that the proposed models can increase upstream operators’ profitability by several million U.S. dollars. © 2016 American Institute of Chemical Engineers AIChE J, 62: 2296–2323, 2016
Author	Drouven, Markus G. Grossmann, Ignacio E.
Author_xml	– sequence: 1 givenname: Markus G. surname: Drouven fullname: Drouven, Markus G. organization: Dept. of Chemical Engineering, Carnegie Mellon University, PA, 15213, Pittsburgh – sequence: 2 givenname: Ignacio E. surname: Grossmann fullname: Grossmann, Ignacio E. email: grossmann@cmu.edu organization: Dept. of Chemical Engineering, Carnegie Mellon University, PA, 15213, Pittsburgh
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Snippet	In this work we address the long‐term, quality‐sensitive shale gas development problem. This problem involves planning, design, and strategic decisions such as... In this work we address the long-term, quality-sensitive shale gas development problem. This problem involves planning, design, and strategic decisions such as...
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SubjectTerms	Chemical engineering Chemical engineers Decisions Design engineering Development strategies Mathematical models mixed-integer programming Natural gas exploration Nonlinear programming Oil shale Petroleum engineering planning scheduling Shale gas Shales Strategy
Title	Multi-period planning, design, and strategic models for long-term, quality-sensitive shale gas development
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