7 datasets found
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Federal
Processed Lab Data for Neural Network-Based Shear Stress Level Prediction
Department of Energy —
Machine learning can be used to predict fault properties such as shear stress, friction, and time to failure using continuous records of fault zone acoustic... -
Federal
Utah FORGE: Slide-Hold-Slide Experiments on Gneiss at Increased Temperature
Department of Energy —
Included are data from triaxial, single-inclined-fracture friction experiments. The experiments were performed with slide-hold-slide protocol on Utah FORGE gneiss at... -
Federal
Utah FORGE: Fault Shear Reactivation Experimental Data for Fluid Injection-Rate Controls on Seismic Moment
Department of Energy —
Included are experimental data recorded from shear experiments that specifically explore the link between fluid-injection rate and seismic moment resulting from shear... -
Federal
Utah FORGE: Pump and Probe Test on an Intact Westerly Granite Sample
Department of Energy —
This dataset contains results from a pump and probe experiment conducted on an intact Westerly Granite sample with a diameter of 1 inch and a height of 1 3/8 inches.... -
Federal
Utah FORGE: Pump and Probe Test on a Mated Fracture Westerly Granite Sample
Department of Energy —
This dataset contains results from a pump and probe experiment conducted on a mated fracture Westerly Granite sample with a diameter of 1 inch and a height of 2 7/8... -
Federal
Data Arrays for Microearthquake (MEQ) Monitoring using Deep Learning for the Newberry EGS Sites
Department of Energy —
The 'Machine Learning Approaches to Predicting Induced Seismicity and Imaging Geothermal Reservoir Properties' project looks to apply machine learning (ML) methods to... -
Federal
Active Source Seismic (Ultrasonic) Data from Double-Direct Shear Lab Experiments
Department of Energy —
Active source ultrasonic data from lab experiments p5270 and p5271 including raw waveforms (WF) and mechanical data (mat). From the PSU team working on the "Machine...
7 datasets found