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WHOLESCALE Modeling of Hydro-Mechanical Processes at San Emidio, Nevada, U.S. on Time Scales of Days

Xi LUO, Chris SHERMAN, Kurt L. FEIGL, John MURPHY, John AKERLEY, Hiroki SONE, Michael A. CARDIFF, Jesse HAMPTON, Hao GUO, Neal E. LORD, Peter E. SOBOL, Clifford H. THURBER, and Herbert F. WANG

Key words
WHOLESCALE, San Emidio, EGS, GPS, FEM
Conference
Stanford Geothermal Workshop
Year
2024
Session
Enhanced Geothermal Systems
Language
English
Paper number
Luo

Full text

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Abstract

The WHOLESCALE acronym stands for Water & Hole Observations Leverage Effective Stress Calculations and Lessen Expenses. The goal of the WHOLESCALE project is to simulate the spatial distribution and temporal evolution of stress in the geothermal system at San Emidio in Nevada, United States. The WHOLESCALE team is taking advantage of the perturbations created by changes in pumping operations during planned shutdowns in 2016, 2021, and 2022 to infer temporal changes in the state of stress in the geothermal system. This rheological experiment is based on the key idea that increasing pore-fluid pressure reduces the effective normal stress acting across preexisting faults. We are developing a fully coupled, hydro-mechanical (H-M) numerical model to describe seismic observations during the shutdowns using the open-source GEOS code developed at Lawrence Livermore National Laboratory. To construct the model configuration and set values for the material properties, we build on a 3-dimensional geologic and structural model of the reservoir that was updated in 2022 from earlier studies. To constrain the modeled values of permeability, we build on a sensitivity analysis of 3-dimensional hydrologic models of the San Emidio reservoir during transient events such as plant flow tests and temporary, planned shutdowns. To specify the initial conditions and boundary conditions for the mechanical simulation, we use several indicators of stress. The fluid-flow boundary conditions for the models are driven by flow rates recorded at production and injection wells. In refining the models, we consider two different time scales. In this paper, we focus on short time scales on the order of minutes to days. In a companion paper (Feigl et al., this meeting), we consider long time scales of the order of years. To validate the modeling, we consider microseismic events recorded over ten days in December 2016 by a seismic array deployed before, during, and after a planned shutdown in December 2016 In this paper, we provide a snapshot of work in progress.

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