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GeoThermalCloud framework for fusion of big data and multi-physics models in Nevada and Southwest New Mexico

Mar 29, 2021
179.87 MB
Publicly accessible
Our GeoThermalCloud framework is designed to process geothermal datasets using a novel toolbox for unsupervised and physics-informed machine learning called SmartTensors. More information about GeoThermalCloud can be found at the GeoThermalCloud GitHub Repository. More information...
Authors
Vesselinov, V. Los Alamos National Laboratory
geothermalenergymachine-learningnew mexicobradynevadagreat basinsouthwest new mexicomulti-physicsbrady hot springssmarttensorsgeothermalcloudgeothermal cloudlos alamos national laboratorysite datasimulationmachine learningmodel

Data for Uncontained Ruptures Reduce Energetics of Triggered Seismicity: Laboratory Fault Reactivation Experiments

Apr 13, 2026
43.25 MB
Publicly accessible
The dataset contains raw mechanical data from laboratory fault reactivation experiments on pre-stressed granite/granitoid samples, along with experimental parameters and MATLAB processing code for data deduction. The raw time-series data were recorded using a triaxial-shear appara...
Authors
Elsworth, D. et al Pennsylvania State University
injection-induced seismicityfault pre-stressseismic moment scalingrupture regimesinduced seismicitytriggered seismicityfault reactivationfluid injectionearthquake magnitudeforecastingrupture mechanicscontained ruptureuncontained ruptureseismic momentlaboratory experimentsraw datatriaxial sheargranitegranitoidgeomechanicsshear displacementaxial displacementmatlab
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  • The GDR provides free access to data generated from projects funded by the U.S. Department of Energy's Office of Geothermal.
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