An analysis of stochastic discrete fracture networks on shale gas recovery

Abstract Complex fracture networks are created by hydraulic fracturing in shale gas reservoirs. The well performance is largely affected by the geometrical properties of fracture networks. It is difficult to estimate well performance because a large number of parameters are used for characterization of a fracture network. In this study, only two parameters are screened to estimate the shale gas recovery by the method of design of experiments. Synthetic fracture networks are generated based on the stochastic theory to represent the secondary fractures in the hydraulic fracture network. Two numerical experiments are designed to correlate the fracture network properties to gas recovery estimated by a commercial software. Various fracture network parameters derived from the analyses of fracture intersection, fractal and percolation are screened to correlate the gas recovery. In terms of the internal structure of a fracture network, a dimensionless parameter called the effective fracture density is proposed to estimate shale gas recovery. It is a combination of the number of fractures, fracture length and orientation. In terms of the boundary of a fracture network, the shale gas recovery is determined by the number of intersection points between the primary fractures and secondary fractures (NIPS). The shale gas recovery predicted by the two parameters (the NIPS and the dimensionless fracture density) is accurate compared with that calculated by the commercial software, which provides us a practical method to estimate the gas recovery by eliminating the number of parameters used for fracture network properties.