Multistage hydraulic fractured horizontal wells (MHFHWs) are widely used in most shale gas reservoirs around the world. Hydraulic fracturing treatment can create hydraulic fractures and activate existing natural fractures to generate a complex fracture network to significantly improve the well performance. For precise production prediction, it is critical to recongnize the spatial extent and properties of the hydraulic fracture network with multiple data such as production history, microseismic et al.
In this study, a novel method that combines the automatical history matching technology and embedded discrete fracture modeling (EDFM) is proposed for the recongnizing the spatial extent and properties of fracture network for MHFHWs. For each hydraulic fracturing stage, the fracture network is parameterized by a set of uncertain parameters, including the length of major fracture, width of the stimulated area, fracture density, fracture permeability, etc. Using these parameters, realizations of the fracture network are generated. The production predictions are obtained by running reservoir simulations with EDFM in which all fractures are embedded into a background grid system, and the automatical history matching method is applied to perform history matching. The proposed approach is validated using synthetic single- well and double-well cases. The results show that the spatial extent and properties of the hydraulic fracture network can be well recognized and that the production history can be well matched.
Considering that microseismic surveillance is often currently performed in shale gas reservoirs, the prior constraint of microseismic data is also investigated in this work. When microseismic data are available, an area with effective microseismic events for each fracturing stage is first defined. The events within the effective area are used to generate discrete fractures, and the events outside of the effective area are abandoned. Furthermore, the shape parameters of the area with effective microseismic events (wet events) are gradually modified by assimilating the production data. A real field case with microseismic data in the Sichuan Basin of China is investigated to test the performance of the proposed method. Reasonable results are obtained, thus demonstrating the robustness of the proposed approach.