An optimization framework for the integration of water management and shale gas supply chain design

Abstract

11This study presents the mathematical formulation and implementation of a 12 comprehensive optimization framework for the assessment of shale gas resources. The

Quantum computing for energy systems optimization: Challenges and opportunities

“…Another such example of an integrated optimization framework for energy supply chain involves optimization of a quadratic constrained mixed-integer problem with 8,321 total variables and 7,247 constraints. Solving this problem by a classical CPU-based solver requires 15.6 hours of computation time [26]. Although energy systems problems have been well acknowledged by industry and academia, most of the existing studies are limited to regional scales.…”

Development of Shale Gas Supply Chain Network under Market Uncertainties

“…This assumption differs from some previous approaches, which considered variability of composition in different shale sites [6,16,17]; (2) The number of wells that can be drilled and hydro-fracture in a shale site in each time period is bounded. Moreover, the maximum number of wells that can be drilled in each shale site throughout the planning horizon is also known beforehand; (3) Multiple wells in the same shale site can be drilled, hydro-fractured, and completed in the same period; (4) A quarterly discretization is considered for the planning horizon of the shale gas project; (5) Well productivity rate is formulated based on the well age; (6) Flowback water represents a fraction of the fracking water utilized during the hydraulic operations in each shale site; (7) Produced water in different shale sites is proportional to the shale gas production in that site; (8) Different management options can be utilized to handle the wastewater generated in each shale site due to the hydro-fracturing activities; (9) Shale sites are located in a region without the necessary pipeline and processing infrastructure.…”

Shale gas pad development planning under price uncertainty

“…Following the work of Cafaro and Grossmann, Drouven and Grossmann propose an MINLP model that involves planning, design, and strategic decisions such as where, when, and how many shale gas wells to drill, where to lay out gathering pipelines, as well as which delivery agreements to arrange. Guerra et al propose an optimization framework for the integration of water management and shale gas supply chain design. Gao and You propose an MINLP model that addresses the life cycle economic and environmental optimization of shale gas supply chain network design and operations.…”