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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. Penn State University
Jul 08, 2022
2 Resources
Publicly accessible

3D Seismic Reflection Attributes of a Geothermal Area

Images from a 3D seismic reflection survey across a geothermal area are shown. Images of coherency and acoustic impedance are shown. Well tracks and MEQ location are overlain.
J., R. Lawrence Livermore National Laboratory
Sep 15, 2014
1 Resources
Publicly accessible

ALFA Biological Monitoring Density Values South Energy Test Site, Newport, Oregon

Density values from active acoustic measurements at South Energy Test Site. This data correspond to a bottom mounted upward-looking WBAT, deployed from April 19th to September 30th. Samples (175 pings) were collected hourly at 1Hz.
Horne, J. Northwest National Marine Renewable Energy Center
Apr 11, 2017
2 Resources
Publicly accessible

ALFA Field Testing of a Dual Sonar System for Detecting Woody Debris

Field testing of a dual sonar system for detecting woody debris in natural settings was conducted at the Tanana River Test Site (TRTS) in Nenana, AK between 8/26 and 9/23, 2015. The TRTS is approximately 65 miles south of Fairbanks and is well suited for testing hydrokinetic energ...
Kasper, J. University of Alaska Fairbanks
Apr 11, 2022
16 Resources
Publicly accessible

Utah FORGE: Seismic Reflection Data

This is 2D and 3D seismic reflection data from Utah FORGE Phase 2c. The readme file containing an explanation of the data including data formats, software that can be used, processing, and projection and datum used. For all 3D and 2D data the following datasets were created and ou...
Miller, J. Energy and Geoscience Institute at the University of Utah
Jun 19, 2019
2 Resources
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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
3 Resources
Publicly accessible
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