Risk Management of Shale Gas Supply Chain under Estimated Ultimate Recovery Uncertainty

Jiyao Gao, Fengqi You

Research output: Chapter in Book/Report/Conference proceedingChapter

3 Scopus citations


This paper addresses the risk management for optimal design and operations of shale gas supply chains under uncertainty of estimated ultimate recovery (EUR). A multiobjective two-stage stochastic mixed-integer linear programming model is proposed to optimize the expected total cost and the financial risk. The latter criterion is measured by conditional value-at-risk (CVaR) and downside risk. In this model, both design and planning decisions are considered with respect to shale well drilling, shale gas production, processing, multiple end-uses, and transportation. In order to solve this computationally challenging problem, we integrate both the sample average approximation method and the L-shaped method. The proposed model and solution methods are illustrated through a case study based on the Marcellus shale play. According to the optimization results, the stochastic model provides a feasible design for all the scenarios with the lowest expected total cost. Moreover, after risk management, total expected cost increases but the risk of high-cost scenarios is reduced effectively, and the CVaR management shows its advantage over downside risk management in this specific case study.

Original languageEnglish (US)
Title of host publication26 European Symposium on Computer Aided Process Engineering, 2016
EditorsZdravko Kravanja, Milos Bogataj
PublisherElsevier B.V.
Number of pages6
ISBN (Print)9780444634283
StatePublished - Jan 1 2016

Publication series

NameComputer Aided Chemical Engineering
ISSN (Print)1570-7946


  • estimated ultimate recovery
  • risk management
  • shale gas
  • uncertainty

ASJC Scopus subject areas

  • Chemical Engineering(all)
  • Computer Science Applications


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