Estimating individual hydraulic fracture conductivity in enhanced geothermal systems using distributed strain sensing and thermo-hydro-mechanical modeling

Accurately quantifying the conductivity of individual hydraulic fractures is critical for optimizing fluid circulation and sustaining performance in Enhanced Geothermal Systems (EGS). Traditional methods, such as pressure transient analysis, yield average conductivity estimates across multiple fractures, limiting insights into individual fracture behavior. In this study, we present a novel integrated approach that combines high-resolution Distributed Strain Sensing (DSS) data with fully coupled thermo-hydro-mechanical (THM) modeling to quantitatively estimate the conductivity of individual fractures created during the stimulation of a horizontal injection well at Fervo Energy’s Project Red. Rayleigh Frequency Shift DSS data collected along the offset production well during the injection test revealed distinct strain responses corresponding to (1) fracture opening from fluid injection and (2) closure when pumping stopped. We simulate the strain response using a THM model, incorporating field-derived boundary conditions and model parameters, pressure falloff analysis, and a Stimulated Reservoir Volume (SRV) characterized using field data. By history-matching the simulated and observed strain responses, we estimate individual fracture conductivities ranging from 190 to 335 mD-ft. Sensitivity analysis highlights the role of matrix permeability, fracture permeability, SRV size, and SRV permeability on the strain response and implications for EGS operations. Our results validate DSS as an effective diagnostic tool for not only detecting hydraulic fracture signals but also quantitatively estimating individual fracture conductivity and flow conformance, thereby enabling more precise management strategies to optimize heat extraction efficiency in EGS reservoirs.