The Utah Frontier Observatory for Research in Geothermal Energy (FORGE) project conducted an eight-stage, commercial-scale hydraulic stimulation of the geothermal reservoir from the injection well 16A(78)-32 in 2024, aiming to establish connectivity with production well 16B(78)-32 and increase the permeability of the geothermal reservoir between the wells. Fiber optic monitoring during the stimulation and subsequent circulation tests confirmed multiple fractures (created or reactivated) intersecting the production well. This paper analyzes the reservoir stimulation, considering hydraulic fracturing and reactivation of pre-existing natural fractures (discrete fracture network, DFN). The analysis uses XSite, a numerical software, to simulate hydraulic fracturing in naturally fractured rock masses. XSite employs the lattice approach to implement the synthetic rock mass (SRM) method. Fully coupled hydro-mechanical simulations were conducted for three single-cluster stages (stages 4, 5 and 10) and two multi-cluster stages (stages 8 and 9), with predicted bottomhole pressures compared to field data. The data on hydraulic and natural fracture geometries and interactions are limited. The DFN geometrical properties, characterized by using borehole logs, are inherently variable and stochastic. The DFN hydromechanical properties are also uncertain and variable, and difficult to characterize on the relevant scale. To better understand the injection pressure measurements, three DFN scenarios and one sensitivity case were explored: 1) permeable and frictional DFN, 2) permeable and cohesive DFN, 3) impermeable and cohesive DFN, and 4) a variant of the impermeable and cohesive DFN with reduced initial aperture (compared to scenario 3). Our findings indicate that DFN characteristics significantly influence reservoir stimulation and injection pressure history. The impermeable and cohesive DFN scenario with reduced aperture best matches the observed long-term bottomhole pressures in most stages. Additionally, fluid migration patterns deviated from classical hydraulic fracture growth, as confirmed by fiber optic monitoring, which detected fracture intersections with the production well misaligned with the injection clusters on the injection well. This further emphasizes the role of natural fractures in response of the reservoir to fluid injection and in creating connectivity. These results highlight the need for continued refinement of DFN modeling to improve predictive capabilities in naturally fractured reservoirs and similar rock types.

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