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Utah FORGE 6-3712: Report on a Data Foundation for Real-Time Identification of Microseismic Events
This submission is a technical report for the Probabilistic Estimation of Seismic Response Using Physics Informed Recurrent Neural Networks project. The report describes the process of extracting events from the borehole seismic sensors. To be effective once deployed, the process ...
Williams, J. et al Global Technology Connection, Inc.
Jan 21, 2025
3 Resources
0 Stars
Curated
3 Resources
0 Stars
Curated
Seismic Survey 2016 Data at San Emidio Nevada
Included here are seismic data recorded at the San Emidio Geothermal field in Nevada. This passive seismic data were collected as part of the DOE-funded Subsurface Technology and Engineering R&D (SubTER) project to advance imaging and characterization of geothermal permeability. ...
Lord, N. et al University of Wisconsin Madison
Jan 05, 2016
5 Resources
0 Stars
Curated
5 Resources
0 Stars
Curated
PoroTomo Natural Laboratory Horizontal and Vertical Distributed Acoustic Sensing Data
This dataset includes links to the PoroTomo DAS data in both SEG-Y and hdf5 (via h5py and HSDS with h5pyd) formats with tutorial notebooks for use. Data are hosted on Amazon Web Services (AWS) Simple Storage Service (S3) through the Open Energy Data Initiative (OEDI). Also include...
Feigl, K. et al University of Wisconsin
Mar 29, 2016
20 Resources
1 Stars
Curated
20 Resources
1 Stars
Curated
DCIF Westerly Granite AE Stress Effect Test (Task 3-1)
Directional Cooling-Induced Fracturing (DCIF) experiments were conducted on rectangular Westerly granite blocks (width=depth=4.0", height=2.0"). Liquid nitrogen was poured in a small, 1"-diameter copper cup attached to the top of the sample, and the resulting acoustic emissions (A...
Nakagawa, S. and Trzeciak, M. Lawrence Berkeley National Laboratory
Jul 08, 2021
15 Resources
0 Stars
Publicly accessible
15 Resources
0 Stars
Publicly accessible
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
Publicly accessible
12 Resources
0 Stars
Publicly accessible