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Active Source Seismic (Ultrasonic) Data from Double-Direct Shear Lab Experiments

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 Learning Approaches to Predicting Induced Seismicity and Imaging Geothermal Reservoir Properties" project. The fric...

Marone, C. Pennsylvania State University

May 05, 2021
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Penn State Lab Testing Fluid-Rock Interaction in Geothermal Reservoirs

This project focused on assessment and discovery of fluid-rock interaction in geothermal reservoirs. We accomplished work in four main areas: 1) fracture formation and the relationship between fluid flow and shear failure, 2) assessment of fracture geometry and fluid permeability ...

Madara, B. et al Pennsylvania State University

Jan 01, 2018
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Processed Lab Data for Neural Network-Based Shear Stress Level Prediction

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 emissions. The files are extracted features and labels from lab data (experiment p4679). The features are extracted with a n...

Marone, C. et al Pennsylvania State University

May 14, 2021
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Brady Geothermal Field PoroTomo Laboratory Deployment Map

Map of the PoroTomo Laboratory at Brady Field, Nevada. Map includes locations of GPS Stations, Shaker Stations, Vibroseis Sites, Seismometers, Fiber-Optic Cables, and wells

Lopeman, J. University of Wisconsin

Mar 01, 2016
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Mapping Fracture Network Creation with Microseismicity During EGS Demonstrations

This a report for the project "Mapping Fracture Network Creation with Microseismicity During EGS Demonstrations". Effective enhanced geothermal systems (EGS) require optimal fracture networks for efficient heat transfer between hot rock and fluid. Microseismic mapping is a key too...

Templeton, D. et al Lawrence Livermore National Laboratory

Apr 18, 2014
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