470506 Optimal Integrated Water Management and Shale Gas Supply Chain Planning Under Uncertainty
This work deals with the development and implementation of a two-stage stochastic optimization approach for the design and planning of the integrated water management and shale gas supply chain. First, a global sensitivity analysis is carried out using the framework developed by the authors [4, 5] to assess and rank uncertain parameters in the integrated supply chain. Then, a Monte Carlo sampling technique is combined with Sobol’s sensitivity indices [6, 7] to compute the effect of uncertainties on the net present value (NPV) performance metric used in the aforementioned framework. Based on the outcomes of the sensitivity analysis, a two-stage stochastic model involving a Mixed Integer Linear Program (MILP) is developed. The first-stage decisions in this model consist of the investment in drilling and fracturing operations as well as in transportation and processing facilities for both water and shale gas. The second-stage decisions are associated with operational issues related to water management and gas delivery. The potential benefits of modeling uncertainty and implementing stochastic models are quantified through two metrics: expected value of perfect information (EVP) and value of stochastic solution (VSS) . Additionally, scenario reduction approaches are evaluated to mitigate computational challenges.
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