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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Bibliographic Details
Published in:AIChE journal Vol. 62; no. 7; pp. 2296 - 2323
Main Authors: Drouven, Markus G., Grossmann, Ignacio E.
Format: Journal Article
Language:English
Published: New York Blackwell Publishing Ltd 01.07.2016
American Institute of Chemical Engineers
Subjects:
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
Online Access:Get full text
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Summary: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
Bibliography:istex:C67FCC8DBE4B47CA3A1FE9FAE25C7742CC5F2A36
ArticleID:AIC15174
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SourceType-Scholarly Journals-1
ObjectType-Feature-2
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ISSN:0001-1541
1547-5905
DOI:10.1002/aic.15174