The Application of Integrated Assisted History Matching and Embedded Discrete Fracture Model Workflow for Well Spacing Optimization in Shale Gas Reservoirs with Complex Natural Fractures

An appropriate well spacing plan is critical for the economic development of shale gas reservoirs. The biggest challenge optimization interpreting subsurface uncertainties associated with hydraulic and natural fractures. Another existence complex This work applied an integrated workflow in reservoirs Sichuan Basin China both consists five components: data preparation, reservoir simulation, estimated ultimate recovery (EUR) analysis, calculation, optimization. Firstly, multiple realizations thirteen uncertain parameters matrix fractures, including permeability porosity, three relative parameters, fracture height, half-length, width, conductivity, water saturation, number, length, were captured by assisted history matching (AHM). fractures modeled embedded discrete model (EDFM) accurately efficiently. Then, 84 AHM solutions combining scenarios from 517 ft to 1550 would generate 420 simulation cases. After these cases, we forecasted long-term production each scenario. Gas EUR degradation interference imply spacing. net present value (NPV) all be calculated trained K -nearest neighbors (KNN) proxy better understand relationship between NPV. In this study, optimum was determined as 793 ft, corresponding a maximum NPV 18 million USD, contribution