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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
0 Stars
Curated
1 Resources
0 Stars
Curated
Utah FORGE: Microseismic Monitoring Geophone Data from Well 78-32
This submission includes geophone data collected by Schlumberger from Utah FORGE Phase 2C seismic monitoring well 78-32 during stimulation testing of well 58-32. The data are hosted by the Center for High Performance Computing (CHPC) at the University of Utah, and a script for dow...
Pankow, K. University of Utah
Mar 18, 2020
5 Resources
0 Stars
Publicly accessible
5 Resources
0 Stars
Publicly accessible
Utah FORGE Seismicity Associated with the 2019 Well 58-32 Stimulation
This catalog describes the seismicity associated with the 2019 stimulation at Utah FORGE. Containing both matched-filter detections (Dzubay et al., 2022) and Schlumberger-recorded events (detected with a 12-level geophone string), the final combined catalog contains a total of 534...
Pankow, K. University of Utah Seismograph Stations
Apr 30, 2019
1 Resources
0 Stars
Curated
1 Resources
0 Stars
Curated
Utah FORGE: High-Resolution DAS Microseismic Data from Well 78-32
This regards a high-resolution DAS microseismic dataset produced by Silixa from Utah FORGE Phase 2C seismic monitoring well 78-32 during stimulation testing of well 58-32. It is a very large dataset and as such it is currently not directly available on GDR. However, it is availabl...
Martin, T. and Nash, G. Energy and Geoscience Institute at the University of Utah
Oct 20, 2019
5 Resources
0 Stars
Publicly accessible
5 Resources
0 Stars
Publicly accessible
Data Arrays for Microearthquake (MEQ) Monitoring using Deep Learning for the Newberry EGS Sites
The 'Machine Learning Approaches to Predicting Induced Seismicity and Imaging Geothermal Reservoir Properties' project looks to apply machine learning (ML) methods to Microearthquake (MEQ) data for imaging geothermal reservoir properties and forecasting seismic events, in order to...
Zhu, T. Pennsylvania State University
May 05, 2021
4 Resources
0 Stars
Curated
4 Resources
0 Stars
Curated
Utah FORGE: Well 58-32 Stimulation Conference Paper and Data
The U.S. Department of Energy's (U.S. DOE) Frontier Observatory for Research in Geothermal Energy (FORGE) is a field laboratory that provides a unique opportunity to develop and test new technologies for characterizing, creating and sustaining Enhanced Geothermal Systems (EGS) in ...
Best, S. Energy and Geoscience Institute at the University of Utah
Apr 24, 2019
2 Resources
0 Stars
Curated
2 Resources
0 Stars
Curated
EGS Collab Experiment 1: Microseismic Monitoring
The U.S. Department of Energy's Enhanced Geothermal System (EGS) Collab project aims to improve our understanding of hydraulic stimulations in crystalline rock for enhanced geothermal energy production through execution of intensely monitored meso-scale experiments. The first expe...
Schoenball, M. et al Lawrence Berkeley National Laboratory
Jul 29, 2019
45 Resources
0 Stars
Curated
45 Resources
0 Stars
Curated