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Utah FORGE: Core Material Friction Experiments

The following folders contain 3 friction experiments on Utah FORGE core material from depths of 6735 8533ft. The experiment conditions range from 100% relative humidity at room temperature to fluid-saturated at 110C. Experiments were done on both intact samples in a single-direct ...

Marone, C. et al Pennsylvania State University

Mar 15, 2023
7 Resources
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Utah FORGE: Friction-Permeability-Seismicity Laboratory Experiments with Non-Linear Acoustics

Laboratory experimental data on saw-cut interface of Westerly Granite and Utah Forge granitoid rocks. Experiments include velocity-stepping and fluid pressure stepping experiments. Mechanical data from 3 ISCO pumps connected to a Temco pressure vessel measure axial, confining and ...

Eijsink, A. and Elsworth, D. Pennsylvania State University

Jul 08, 2022
2 Resources
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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
1 Resources
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Utah FORGE 5-2419: Seismicity-Permeability Relationships Probed via Nonlinear Acoustic Imaging Workshop Presentation

This is a presentation on the Seismicity-Permeability Relationships Probed via Nonlinear Acoustic Imaging project by Pennsylvania State University, presented by Derek Elsworth. The project's objectives were to explore controls and acoustic signatures of aseismic through seismic e...

Elsworth, D. et al Pennsylvania State University

Sep 08, 2023
1 Resources
0 Stars
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Utah FORGE: Slide-Hold-Slide Experiments on Gneiss at Increased Temperature

Included are data from triaxial, single-inclined-fracture friction experiments. The experiments were performed with slide-hold-slide protocol on Utah FORGE gneiss at increased temperature. With a ~10 MPa normal stress, temperatures vary between experiments from room temperature u...

Eijsink, A. and Elsworth, D. Pennsylvania State University

Jul 25, 2023
24 Resources
0 Stars
Publicly accessible

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...