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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
Appendices for Geothermal Exploration Artificial Intelligence Report
The Geothermal Exploration Artificial Intelligence looks to use machine learning to spot geothermal identifiers from land maps. This is done to remotely detect geothermal sites for the purpose of energy uses. Such uses include enhanced geothermal system (EGS) applications, especia...
Duzgun, H. et al Colorado School of Mines
Jan 08, 2021
12 Resources
0 Stars
Curated
12 Resources
0 Stars
Curated
Envisat Track 349 and Sentinel-1A Track 64 Interferometric Synthetic Aperture Radar Data of Coso Geothermal Field, California, USA, 2004-2016
This submission contains tarred pair directories for interferometric synthetic aperture radar (InSAR) data covering Coso Geothermal Field in California, USA.
Explanation of pair subdirectories:
Pairs are formed using the InSAR processing software GMT5SAR (Sandwell et al., 2011).
...
Reinisch, E. and Feigl, K. University of Wisconsin
Jun 25, 2019
4 Resources
0 Stars
Publicly accessible
4 Resources
0 Stars
Publicly accessible
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