Hydraulic Fractures Simulation and Stimulated Reservoir Volume Estimation for Shale Gas Fracturing

Abstract

Abstract Multi-stage & multi-cluster fracturing in horizontal well drilling is the core technology in for commercial exploitation of shale gas resevoir. According to vast field data, there is remarkable positive correlation relationship between stimulated reservoir volume (SRV) and shale gas production. Hence, estimating the SRV is essential for both pre-fracturing design and post-fracturing evaluation. However, the forming process of SRV involves with many complex mechanisms, making it is difficult to be simulated. In this paper, we establish a mathematical model to estimate the SRV by simulating multiple hydraulic fractures propagate, formation stress change and reservoir pressure rise; consequently, the stress and pressure change might make natural fractures occur tensile failure or shear failure, generating a high-conductivity zone (i.e., SRV) in the shale reservoir. To solve the model, displacement discontinuity method (DDM) is applied to simulate non-planar propagation of multiple hydraulic fractures and calculate formation stress change. Finite difference method (FDM) is used to compute reservoir pressure rise. The natural fractures failure state is determined by tensor formulae derived from Warpinski's failure theory. This SRV estimation method involves a variety of complex but crucial physical mechanisms during shale fracturing process which include unequal flow-rate distribution in different hydraulic fractures, non-planar hydraulic fractures propagation under stress interference, reservoir permeability increases with SRV expanding, two types of natural fracture failure and so on. A field case study was performed to show the dynamic processes of hydraulic fractures propagation, reservoir permeability increase, and the SRV expansion during shale gas fracturing. Then we compared the simulation results with analytical solution, published papers and on-site microseismic monitoring data to verify our model. Finally, the influence of geological condition and engineering parameters on SRV was investigated by sensitivity analysis.