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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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Utah FORGE: Pump and Probe Test on a Mated Fracture Westerly Granite Sample

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 inches. The experiment was performed within an aluminum triaxial pressure vessel (TEMCO) to investigate the non-line...

Klinghammer, H. et al Pennsylvania State University

May 19, 2024
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Utah FORGE: Pump and Probe Test on an Intact Westerly Granite Sample

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. The experiment was performed within an aluminum triaxial pressure vessel (TEMCO) to investigate the non-linear acou...

Klinghammer, H. et al Pennsylvania State University

May 21, 2024
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Imperial Valley Dark Fiber Project Continuous DAS Data

The Imperial Valley Dark Fiber Project acquired Distributed Acoustic Sensing (DAS) seismic data on a ~28 km segment of dark fiber between the cities of Calipatria and Imperial in the Imperial Valley, Southern California. Dark fiber refers to unused optical fiber cables in telecomm...

Ajo-Franklin, J. et al Lawrence Berkeley National Laboratory

Nov 10, 2020
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Utah FORGE 2439: Machine Learning for Well 16A(78)-32 Stress Predictions

This report reviews the training of machine learning algorithms to laboratory triaxial ultrasonic velocity data for Utah FORGE Well 16A(78)-32. Three machine learning (ML) predictive models were developed for the prediction of vertical and two orthogonally oriented horizontal str...

Kelley, M. et al Battelle Memorial Institute

Jun 19, 2023
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EGS Collab Experiment 1: SIMFIP Notch-164 GRL Paper

Characterizing the stimulation mode of a fracture is critical to assess the hydraulic efficiency and the seismic risk related to deep fluid manipulations. We have monitored the three-dimensional displacements of a fluid-driven fracture during water injections in a borehole at ~1.5...

Guglielmi, Y. Lawrence Berkeley National Laboratory

Sep 24, 2020
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Utah FORGE 5-2565: Hydrothermal Evolution of Fracture Properties Workshop Presentation

This is a presentation on the Evolution of Permeability and Strength Recovery of Shear Fractures Under Hydrothermal Conditions project by the U.S. Geological Survey, presented by Dr. David Lockner. The project's objective was to determine how thermal, hydraulic, mechanical, and ch...

Lockner, D. et al United States Geological Survey

Sep 08, 2023
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Hawthorne Nevada Deep Direct-Use Feasibility Study 3D Geologic Model

The objective of this project is to use a multi-disciplinary, three-tiered approach to assess the geothermal resource and determine the feasibility of implementing a large-scale, direct-use facility for the Hawthorne Army Depot (HAD) and the various town and county facilities in H...

Lowry, T. Nevada Bureau of Mines and Geology

Mar 29, 2018
3 Resources
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Utah FORGE: Well 58-32 Schlumberger FMI Logs DLIS and XML files

This zipped data set includes Schlumberger FMI logs DLIS and XML files from Utah FORGE deep well 58-32. These include runs 1 (2226-7550 ft) and 2 (7440-7550 ft). Run 3 (7390-7527ft) was acquired during phase 2C.

Nash, G. and Moore, J. Energy and Geoscience Institute at the University of Utah

Nov 17, 2017
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WISE-CASING: Time Domain Reflectometry Data from Cymric Field, CA

The objective of this field test is to validate several technologies for non-invasive well integrity assessment using existing wells with a known completion. The tests were made at the Cymric oil field, which is a steam flood operation. The wells therefore undergo similar downhole...

Wang, J. Lawrence Berkeley National Laboratory

Feb 21, 2019
5 Resources
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