Distributionally Robust Optimization of Shale Gas Supply Chains under Uncertainty

This paper aims to leverage the big data in shale gas industry for better decision making in optimal design and operations of shale gas supply chains under uncertainty. We propose a two-stage distributionally robust optimization model, where uncertainties associated with both the upstream shale well estimated ultimate recovery and downstream market demand are simultaneously considered. In this model, decisions are classified into first-stage design decisions, which are related to drilling schedule, pipeline installment, and processing plant construction, as well as second-stage operational decisions associated with shale gas production, processing, transportation, and distribution. A data-driven approach is applied to construct the ambiguity set based on principal component analysis and first-order deviation functions. By taking advantage of affine decision rules, a tractable mixed-integer linear programming formulation can be obtained. The applicability of the proposed modeling framework is demonstrated through a case study of Marcellus shale gas supply chain. Comparisons with alternative optimization models are investigated as well.

[1]  F. You,et al.  Game theory approach to optimal design of shale gas supply chains with consideration of economics and life cycle greenhouse gas emissions , 2017 .

[2]  Fengqi You,et al.  Deciphering and handling uncertainty in shale gas supply chain design and optimization: Novel modeling framework and computationally efficient solution algorithm , 2015 .

[3]  Fengqi You,et al.  Design and optimization of shale gas energy systems: Overview, research challenges, and future directions , 2017, Comput. Chem. Eng..

[4]  Ignacio E. Grossmann,et al.  Optimization models for shale gas water management , 2014 .

[5]  J. D. Hughes,et al.  Energy: A reality check on the shale revolution , 2013, Nature.

[6]  Fengqi You,et al.  Dynamic Material Flow Analysis-Based Life Cycle Optimization Framework and Application to Sustainable Design of Shale Gas Energy Systems , 2018, ACS Sustainable Chemistry & Engineering.

[7]  Omar J. Guerra,et al.  An optimization framework for the integration of water management and shale gas supply chain design , 2016, Comput. Chem. Eng..

[8]  Yinyu Ye,et al.  Distributionally Robust Optimization Under Moment Uncertainty with Application to Data-Driven Problems , 2010, Oper. Res..

[9]  J. M. Ponce-Ortega,et al.  Optimal Water Management under Uncertainty for Shale Gas Production , 2016 .

[10]  Xuan Vinh Doan,et al.  Models for Minimax Stochastic Linear Optimization Problems with Risk Aversion , 2010, Math. Oper. Res..

[11]  Fengqi You,et al.  A computational framework and solution algorithms for two‐stage adaptive robust scheduling of batch manufacturing processes under uncertainty , 2016 .

[12]  F. You,et al.  Shale Gas Supply Chain Design and Operations toward Better Economic and Life Cycle Environmental Performance: MINLP Model and Global Optimization Algorithm , 2015 .

[13]  Melvyn Sim,et al.  Adaptive Distributionally Robust Optimization , 2019, Manag. Sci..

[14]  Chao Shang,et al.  Distributionally robust optimization for planning and scheduling under uncertainty , 2018, Comput. Chem. Eng..

[15]  A. Ben-Tal,et al.  Adjustable robust solutions of uncertain linear programs , 2004, Math. Program..

[16]  Yongpei Guan,et al.  Data-driven risk-averse stochastic optimization with Wasserstein metric , 2018, Oper. Res. Lett..

[17]  I. Jolliffe.  Principal Component Analysis , 2002, International Encyclopedia of Statistical Science.

[18]  Daniel Kuhn,et al.  Distributionally Robust Convex Optimization , 2014, Oper. Res..

[19]  Ignacio E. Grossmann,et al.  Strategic planning, design, and development of the shale gas supply chain network , 2014 .

[20]  F. You,et al.  A data-driven multistage adaptive robust optimization framework for planning and scheduling under uncertainty , 2017 .

[21]  Mahmoud M. El-Halwagi,et al.  Optimal Planning of Infrastructure for the Supply Chain of Shale Gas , 2017 .

[22]  Fengqi You,et al.  Optimal design and operations of supply chain networks for water management in shale gas production: MILFP model and algorithms for the water‐energy nexus , 2015 .