Accurate construction of a shale-reservoir fracture network is a prerequisite for optimizing the fracturing methods and determining shale-gas extraction schemes. Considering the influence of geological conditions, stress levels, desorption–adsorption, and fissure characteristics and distribution, establishing a shale-gas reservoir fracture-network model based on a random fracture network is significant. According to the discrete network model and Monte Carlo stochastic theory, the random fracture network of natural and artificial fractures in a shale-gas reservoir stimulation zone was constructed in this study. The porosity and permeability of the stimulation zone were calculated according to the network geometric properties. The fracture network was reconstructed, and the fissure connectivity was characterized. Numerical simulation of the seepage flow was performed for shale-gas reservoirs with different fracking-fracture combinations. The results showed that the local permeability dominated by the main fracture was the main factor that affected the initial shale-gas production efficiency. The total shale-gas productivity was mainly controlled by the effective stimulated volume. The evenly distributed secondary fracture network could effectively improve the effective stimulated volume of the stimulation zone. A 4% increase in the effective stimulated volume could improve the accumulated gas production by approximately 12%. Moreover, when the ratio of the main fracture to the secondary fracture was approximately 1:14, the accumulated gas production was optimized.
A smart productivity evaluation method for shale gas wells based on 3D fractal fracture network model
