Application of a Novel Multiobjective Optimization Framework for Optimizing Hydraulic Fracture Parameters in Shale Gas Reservoirs

Summary Optimization of hydraulic fracture parameters is a crucial step in shale gas development. In this paper, we use the Barnett Shale as a case study and develop a comprehensive multiobjective optimization framework for high-dimensional hydraulic fracture parameters. The goal is to identify the globally optimal parameter combination that maximizes cumulative gas production and net present value (NPV) while minimizing carbon emissions. A progressive strategy is used to iteratively optimize the objective function, utilizing a fourth-order polynomial surrogate model to significantly reduce the number of numerical simulations while maintaining prediction accuracy. A comparative analysis using analysis of variance, Sobol sensitivity analysis, and Shapley additive explanations (SHAP) reveals that fracture height, number, permeability, and width constitute the critical influencing parameters. Additionally, an innovative comprehensive weighting model is proposed, assigning weights of 0.323, 0.448, and 0.229 to cumulative gas production, NPV, and carbon emissions, respectively. Finally, the grey relational analysis (GRA) method is integrated into the comprehensive distance-based ranking (COBRA) framework to develop a GRA-COBRA multicriteria decision-making (MCDM) model. This model ranks the Pareto solution set obtained from the multiobjective optimization to determine the optimal combination of hydraulic fracture parameters. This framework offers a novel approach for the efficient optimization and decision-making of high-dimensional hydraulic fracture parameters in shale gas reservoirs.