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

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...

Vesselinov, V. Los Alamos National Laboratory

Mar 29, 2021
4 Resources
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Utah FORGE: Fault Shear Reactivation Experimental Data for Fluid Injection-Rate Controls on Seismic Moment

Included are experimental data recorded from shear experiments that specifically explore the link between fluid-injection rate and seismic moment resulting from shear reactivation of laboratory faults. Raw mechanical data from three experiments are included alongside corresponding...

Roseboom, M. et al Pennsylvania State University

Nov 07, 2023
6 Resources
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Publicly accessible

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

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...

Elsworth, D. et al Pennsylvania State University

Apr 13, 2026
15 Resources
0 Stars
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GeoThermalCloud framework for fusion of big data and multi-physics models in Nevada and Southwest New Mexico

Utah FORGE: Fault Shear Reactivation Experimental Data for Fluid Injection-Rate Controls on Seismic Moment

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