Strategic planning, design, and development of the shale gas supply chain network

The long‐term planning of the shale gas supply chain is a relevant problem that has not been addressed before in the literature. This article presents a mixed‐integer nonlinear programming (MINLP) model to optimally determine the number of wells to drill at every location, the size of gas processing...

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Vydané v:AIChE journal Ročník 60; číslo 6; s. 2122 - 2142
Hlavní autori: Cafaro, Diego C., Grossmann, Ignacio E.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York Blackwell Publishing Ltd 01.06.2014
American Institute of Chemical Engineers
Predmet:
Byproducts
Chemical engineering
Drilling
Economics
Hydraulic fracturing
Hydrocarbons
Long-term planning
mixed-integer nonlinear programming approach
Natural gas
Nonlinear programming
Objective function
Oil shale
Optimization
Position (location)
Process engineering
Shale gas
Shales
solution algorithm
strategic plan
Strategic planning
supply chain
Supply chains
ISSN:0001-1541, 1547-5905
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Shrnutí:The long‐term planning of the shale gas supply chain is a relevant problem that has not been addressed before in the literature. This article presents a mixed‐integer nonlinear programming (MINLP) model to optimally determine the number of wells to drill at every location, the size of gas processing plants, the section and length of pipelines for gathering raw gas and delivering processed gas and by‐products, the power of gas compressors, and the amount of freshwater required from reservoirs for drilling and hydraulic fracturing so as to maximize the net present value of the project. Because the proposed model is a large‐scale nonconvex MINLP, we develop a decomposition approach based on successively refining a piecewise linear approximation of the objective function. Results on realistic instances show the importance of heavier hydrocarbons to the economics of the project, as well as the optimal usage of the infrastructure by properly planning the drilling strategy. © 2014 American Institute of Chemical Engineers AIChE J, 60: 2122–2142, 2014
Bibliografia:ArticleID:AIC14405
istex:42EE462ACC85218728F3FB5B4D53EA463CE0FCA6
Fulbright Commission Argentina
CAPD at Carnegie Mellon University
CONICET
ark:/67375/WNG-DM2Z9M24-P
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ISSN:0001-1541
1547-5905
DOI:10.1002/aic.14405