Stochastic programming approach to optimal design and operations of shale gas supply chain under uncertainty

Jiyao Gao, Fengqi You*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

In this paper, we propose the first stochastic model addressing the optimal design and operations of the comprehensive shale gas supply chain, where uncertainties of estimated ultimate recovery (EUR) in each shale well are considered. The resulting mixed-integer linear programming (MILP) model covers the well-to-wire life cycle of shale gas, which consists of a number of stages including freshwater acquisition, shale well drilling, fracking, and completion, shale gas production, wastewater management, shale gas processing, electricity generation as well as transportation and storage. In order to reduce the model size and the number of scenarios, we use a sample average approximation approach to generate scenarios based on the EUR distribution derived from actual historical data. To demonstrate the proposed stochastic model and solution approach, we present a case study based on Marcellus shale play to maximize the total expected profit of this shale gas supply chain network.

Original languageEnglish (US)
Title of host publication54rd IEEE Conference on Decision and Control,CDC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages6656-6661
Number of pages6
ISBN (Electronic)9781479978861
DOIs
StatePublished - Feb 8 2015
Event54th IEEE Conference on Decision and Control, CDC 2015 - Osaka, Japan
Duration: Dec 15 2015Dec 18 2015

Publication series

NameProceedings of the IEEE Conference on Decision and Control
Volume54rd IEEE Conference on Decision and Control,CDC 2015
ISSN (Print)0743-1546

Other

Other54th IEEE Conference on Decision and Control, CDC 2015
CountryJapan
CityOsaka
Period12/15/1512/18/15

Keywords

  • Natural gas
  • Stochastic processes
  • Supply chains
  • Transportation
  • Uncertainty
  • Wastewater

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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