Title: |
WHOLESCALE Modeling of Hydro-mechanical Processes at San Emidio, Nevada, U.S. on Time Scales of Years |
Authors: |
Kurt L. FEIGL, Xi LUO, Chris SHERMAN, CorneĢ KREEMER, Sam A. BATZLI, Michael A. CARDIFF, and Herbert F. WANG |
Key Words: |
WHOLESCALE, San Emidio, EGS, GPS, INSAR, FEM |
Conference: |
Stanford Geothermal Workshop |
Year: |
2024 |
Session: |
Enhanced Geothermal Systems |
Language: |
English |
Paper Number: |
Feigl |
File Size: |
2505 KB |
View File: |
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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. To reach this goal, the WHOLESCALE team is developing a fully coupled, thermo-hydro-mechanical (T-H-M) numerical model to describe geodetic observations during the shutdowns using the open-source GEOS code developed at Lawrence Livermore National Laboratory (Settgast et al., 2018). In refining the models, we consider two different time scales. In this paper, we focus on long time scales of the order of years. In a companion paper (Xi LUO et al., this meeting), we consider short time scales on the order of minutes to days. To calibrate the model, we consider two types of geodetic data: GPS (Global Positioning System) and InSAR (Interferometric Synthetic Aperture Radar). The GPS data set consists of daily time series of displacement in three dimensions. These have been estimated from data collected from two continuously operating stations, SEMS and SEMN, installed on monuments attached to idle wellheads within the geothermal field at San Emidio as well as from a third GPS station, named GARL, located outside the geothermal area in the mountain range to the northeast of the power plant. The shape of the modeled displacement field agrees approximately with that observed by InSAR near the producing wells at the center of the geothermal field. The modeled rate of vertical displacement, however, agrees with that estimated from GPS and InSAR data only to within a factor of four.
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