Title:

Spatial-Temporal Stress Heterogeneity in the Geothermal Reservoir at San Emidio, Nevada, U.S

Authors:

Ben JAHNKE, Hao GUO, Ben HEATH, Erin CUNNINGHAM, Chris SHERMAN, Hiroki SONE, Ian WARREN, Corné KREEMER, Clifford H. THURBER, Kurt L. FEIGL, and The WHOLESCALE Team

Key Words:

WHOLESCALE, San Emidio, EGS, Stress, Stress Inversion

Conference:

Stanford Geothermal Workshop

Year:

2022

Session:

Enhanced Geothermal Systems

Language:

English

Paper Number:

Jahnke

File Size:

1930 KB

View File:

Abstract:

We attempt to constrain models of the reservoir stress of a geothermal reservoir in San Emidio, Nevada, which will be used in a reservoir-scale hydro-mechanical numerical model. Our reservoir stress models are based on (1) the densities of subsurface lithologies, (2) surface topography, (3) the relative magnitudes of the total vertical stress (SV), maximum horizontal stress (SHmax), and minimum horizontal stress (Shmin), and (4) the azimuth of SHmax. The models are informed from stress indicators within a ~175 km radius of San Emidio which provides constraints on (1) the relative magnitudes of SV, SHmax, and Shmin, and (2) the azimuth of SHmax. To evaluate how well the model represents the reservoir stress, focal mechanism data from microseismic events which occurred within the reservoir during a plant shutdown in 2016 are used. Stress inversions (Vavryčuk, 2014) of the focal mechanism data estimate the in situ principal stress orientations, their relative magnitudes, and preferred nodal planes. Then the principal orientations of the model stresses at the locations of microseismic events were compared to the principal stress orientations inverted from the focal mechanisms. These analyses allow us to refine the reservoir stress model that agrees with field observations and is therefore suitable to use to forward model the reservoir responses against production and injection operations. In this paper, we provide a snapshot of work in progress, including the highlights listed in the conclusions below. The work presented herein has been funded in part by the Office of Energy Efficiency and Renewable Energy (EERE), U.S. department of Energy, under Award Numbers DE-EE0007698 and DE-EE0009032.


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