The most effective method for stimulating shale gas reservoirs is horizontal wells with successful multi-stage hydraulic fracture treatments. Recent fracture diagnostic technologies such as microseismic technology have shown that complex fracture networks are commonly created in the field. However, often times, the stimulated reservoir volume (SRV) obtained from the microseismic interpretation does not provide propped fracture volume and its conductivity such that, commonly, there is a difference between the SRV that is open for the gas flow and SRV obtained from microseismic diagnosis.

In this paper, the coupled hydraulic fracturing model that is capable to simulate dynamic fracture propagation, reservoir flow simulation, the interactions between hydraulic fractures and pre-existing natural fractures, and proppant transportation will be used to conduct numerical experiments. The effects of proppant size, horizontal differential stress, fracture fluid viscosity, pumping rate, and natural fracture spacing on the propped stimulated reservoir volume (PSRV) and hydraulic fracture conductivities is then compared and quantified. At last, using the knowledge gathered during parametric studies will be applied to enhance the effectiveness of stimulation.

Simulation results from the parametric studies show that enlarging SRV does not guarantee larger PSRV. Our result shows that thin fluid with viscosity of 1 cp to 2 cp increases SRV but it decrease PSRV because proppants are not distributed further inside of network with thin fluid. Fracture intensity increased in a reservoir with relatively smaller horizontal differential stress and natural fracture spacing. The conductivity of propped fracture network increased when fracture intensity is low and larger proppant size is used. These results will provide a better understanding to enhance SRV, fracture intensity and fracture conductivity through proper proppant, fluid and pumping rate selection depending on the differential stress and the complexity of pre-existing natural fracture network.

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