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Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs Results
Geothermal power plants typically show decreasing heat and power production rates over time. Mitigation strategies include optimizing the management of existing wells increasing or decreasing the fluid flow rates across the wells and drilling new wells at appropriate locations. Th...
Beckers, K. et al National Renewable Energy Laboratory
Oct 20, 2021
6 Resources
0 Stars
Publicly accessible
6 Resources
0 Stars
Publicly accessible
Active Source 3D Seismic Tomography of Brady Hot Springs Geothermal Field, Nevada
We deployed a dense seismic array to image the shallow structure in the injection area of the Brady Hot Springs geothermal site in Nevada. The array was composed of 238 5 Hz, three-component nodal instruments and 8,700 m of distributed acoustic sensing (DAS) fiber-optic cable inst...
Parker, L. University of Wisconsin
Aug 09, 2017
1 Resources
0 Stars
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1 Resources
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3-D Geologic Controls of Hydrothermal Fluid Flow at Brady Geothermal Field, Nevada using PCA
In many hydrothermal systems, fracture permeability along faults provides pathways for groundwater to transport heat from depth. Faulting generates a range of deformation styles that cross-cut heterogeneous geology, resulting in complex patterns of permeability, porosity, and hydr...
Siler, D. and Pepin, J. United States Geological Survey
Oct 01, 2021
4 Resources
0 Stars
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4 Resources
0 Stars
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Brady Hot Springs Seismic Modeling Data for Push-Pull Project
This submission includes synthetic seismic modeling data for the Push-Pull project at Brady Hot Springs, NV. The synthetic seismic is all generated by finite-difference method regarding different fracture and rock properties.
Zhang, R. University of Louisiana
Jul 31, 2018
56 Resources
0 Stars
Publicly accessible
56 Resources
0 Stars
Publicly accessible
Brady's Geothermal Field Nodal Seismometers Metadata
Metadata for the nodal seismometer array deployed at the POROTOMO's Natural Laboratory in Brady Hot Spring, Nevada during the March 2016 testing.
Metadata includes location and timing for each instrument as well as file lists of data to be uploaded in a separate submission.
Parker, L. University of Wisconsin
Mar 28, 2016
12 Resources
0 Stars
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12 Resources
0 Stars
Publicly accessible
PoroTomo: Brady Geothermal Field InSAR Data
Included are links to compressed InSAR pairs covering Brady Geothermal Field for TerraSAR-X (tracks 53, 91, and 167) and Sentinel-1A data. Pairs from the PoroTomo deployment period and pairs forming a minimum spanning tree according to perpendicular baseline are included for Terr...
Reinisch, E. University of Wisconsin
Jul 11, 2017
6 Resources
0 Stars
Publicly accessible
6 Resources
0 Stars
Publicly accessible
Brady's Geothermal Field DAS Earthquake Data
The submitted data correspond to the vibration caused by a 3.4 M earthquake and captured by the DAS horizontal and vertical arrays during the PoroTomo Experiment. Data is available in the original .sgy formats, as well as in standardized .h5 formats.
Earthquake information :
M ...
Feigl, K. University of Wisconsin
Mar 21, 2016
10 Resources
0 Stars
Publicly accessible
10 Resources
0 Stars
Publicly accessible
Brady's Geothermal Field Analysis of Pressure Data
*This submission provides corrections to GDR Submissions 844 and 845*
Poroelastic Tomography (PoroTomo) by Adjoint Inverse Modeling of Data from Hydrology.
The 3 *csv files containing pressure data are the corrected versions of the pressure dataset found in Submission 844. The ...
Lim, D. University of Wisconsin
Mar 17, 2017
6 Resources
0 Stars
Publicly accessible
6 Resources
0 Stars
Publicly accessible
Understanding Constraints on Geothermal Sustainability Through Reservoir Characterization at Brady Geothermal Field, Nevada
The vast supply of geothermal energy stored throughout the Earth and the exceedingly long time required to dissipate that energy makes the world's geothermal energy supply nearly limitless. As such, this resource holds the potential to provide a large supply of the world's energy ...
Patterson, J. University of Wisconsin
Jul 11, 2018
1 Resources
1 Stars
Publicly accessible
1 Resources
1 Stars
Publicly accessible
Machine Learning to Identify Geologic Factors Associated with Production in Geothermal Fields: A Case-Study Using 3D Geologic Data from Brady Geothermal Field and NMFk
In this paper, we present an analysis using unsupervised machine learning (ML) to identify the key geologic factors that contribute to the geothermal production in Brady geothermal field. Brady is a hydrothermal system in northwestern Nevada that supports both electricity producti...
Siler, D. et al United States Geological Survey
Oct 01, 2021
6 Resources
0 Stars
Publicly accessible
6 Resources
0 Stars
Publicly accessible
Brady Geodatabase for Geothermal Exploration Artificial Intelligence
These files contain the geodatabases related to Brady's Geothermal Field. It includes all input and output files for the Geothermal Exploration Artificial Intelligence. Input and output files are sorted into three categories: raw data, pre-processed data, and analysis (post-proces...
Moraga, J. et al Colorado School of Mines
Apr 27, 2021
3 Resources
0 Stars
Publicly accessible
3 Resources
0 Stars
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Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs
Subsurface data analysis, reservoir modeling, and machine learning (ML) techniques have been applied to the Brady Hot Springs (BHS) geothermal field in Nevada, USA to further characterize the subsurface and assist with optimizing reservoir management. Hundreds of reservoir simulat...
Beckers, K. et al National Renewable Energy Laboratory
Feb 18, 2021
1 Resources
0 Stars
Publicly accessible
1 Resources
0 Stars
Publicly accessible