Understanding injected flow behavior through subsurface fractured media is important for successful energy production of enhanced geothermal systems (EGS). The injected fluid travels through stimulated and natural fractures; the fracture surface – matrix interaction leads to heat exchange and energy production. Since the natural and stimulated fractures provide fast paths for flow and fracture connectivity dictates the flow behavior and flow directions, understanding the effect of fracture network topology is important for flow predictions at reservoir sites. We used Discrete Fracture Network (DFN) model to generate fracture configurations, and to simulate flow and transport through fractures. The particle tracking tool was applied to follow particles trajectories travelling through fractures from injection source to production well. The DFN team at EGS Collab performed tremendous work on identification and characterization the fractures observed at wells and boreholes. The Common DFN (CDFN) model, based on deterministically defined fractures observed at boreholes, was generated on FracMan software. We transferred the CDFN to dfnWorks computational model and generated new DFNs where Common DFN is surrounded by stochastic fracture networks, which provide a fracture connectivity for flow paths from stimulated fracture and injection well to the production well and the flowing fractures at monitoring boreholes. We simulated flow and particle tracking through the generated DFNs, and show how flow tortuosity and particles travel distance depend on natural fracture networks intensities. The presented new modeling workflow has a high potential for reproducing exact flow paths observed at the experimental sites with understanding fracture network topology of geothermal reservoirs at large scale.

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