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Distributed Acoustic Sensing (DAS) of Strain at Earth Tide Frequencies: Laboratory Tests

Jan 24, 2018
1.09 GB
Publicly accessible
The solid Earth strains in response to the gravitational pull from the Moon, Sun, and other planetary bodies. Measuring the flexure of geologic material in response to these Earth tides provides information about the geomechanical properties of rock and sediment. Such measurements...
Authors
Coleman, T. and Becker, M. California State University
geothermalenergyearth tidedasdistributed acoustic sensingfiber optics sensorslow frequency straingeomechanicsmeasurementmatlabegslab testsfracturecharacterizationhydraulicstimulation strain

Utah FORGE: Laboratory Experiments Examining the Effect of Thermal and Mechanical Processes on Hydraulic Transmissivity Evolution

Apr 03, 2023
858.13 kB
Publicly accessible
Using laboratory slide-hold-slide experiments, at temperatures from 22 to 200 degrees C, to examine effects of fracture reactivation and quasi-static loading on the evolution of fluid transport properties of simulated fractures in Westerly granite. At all temperatures, the in-plan...
Authors
Lockner, D. et al United States Geological Survey
geothermalenergyutah forgehydraulic transmissivityfluid-rock interactionsshear fracturessealinggranite

3-D Geologic Controls of Hydrothermal Fluid Flow at Brady Geothermal Field, Nevada using PCA

Oct 01, 2021
7.12 MB
Publicly accessible
In many hydrothermal systems, fracture permeability along faults provides pathways for groundwater to transport heat from depth. Faulting generates a range of deformation styles that cross-cut heterogeneous geology, resulting in complex patterns of permeability, porosity, and hydr...
Authors
Siler, D. and Pepin, J. United States Geological Survey
geothermalenergypca3d geologic modelgeologic modelgeologycharacterizationmachine learningmlbhsbrady hot springsprincipal component analysisproductionstressfaultsrbradyhydrothermalgeologic structureunsupervised3d well datacodegeothermicgeophysics

Machine Learning to Identify Geologic Factors Associated with Production in Geothermal Fields: A Case-Study Using 3D Geologic Data from Brady Geothermal Field and NMFk

Oct 01, 2021
5.68 MB
Publicly accessible
In this paper, we present an analysis using unsupervised machine learning (ML) to identify the key geologic factors that contribute to the geothermal production in Brady geothermal field. Brady is a hydrothermal system in northwestern Nevada that supports both electricity producti...
Authors
Siler, D. et al United States Geological Survey
geothermalenergynmfkbrady hot springsmachine learningmlbhsnonnegative matrix factorization k-meanshydrothermalbradyk-meansclusteringnonnegative matrix factorizationmatrix factorizationgeothermalcloudsmarttensorsunsupervised3d well data3d geologic mapgeologic structurefaultsstressgeologycharacterizationgeologic modelproductioncode