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Brady's, NV×

Nevada Production and Injection Well Data for Facilities with Flash Steam Plants

Files contain a summary of the production and injection data submitted by the geothermal operators to the Nevada Bureau of Mines and Geology over the period from 1985 thru 2009
Mines, G. Idaho National Laboratory
Jan 01, 2009
5 Resources
0 Stars
Curated

DASH Slow Strain Rates from Brady Hot Springs Geothermal Field during PoroTomo Deployment Period

This submission contains slow strain rates summed to radians over 30 second intervals [rad/s] derived from horizontal distributed acoustic sensing measurements (DASH) of Brady geothermal field during PoroTomo deployment (2016-Mar-14 to 2016-Mar-26). There is one file correspondin...
Reinisch, E. et al University of Wisconsin
Jun 27, 2018
20 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

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
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

Brady Geothermal Field Borehole Pressure Data

This submission supersedes pressure data from March 2017 which can be found as a link in the submission resources. This submission contains 3 .csv files with time series pressure data in 3 observation wells at Brady Geothermal Field as part of the PoroTomo project. These pressure ...
Cardiff, M. and Lim, D. University of Wisconsin
Apr 01, 2016
4 Resources
0 Stars
Publicly accessible

Raw Pressure Data from Observation Wells at Brady's Hot Springs

This .csv files contain the raw water pressure data from three observation wells during pumping tests performed in the Spring of 2016. Included is a "read me" file explaining the details of where and how the data were collected.
Lim, D. University of Wisconsin
Mar 13, 2016
6 Resources
0 Stars
Publicly accessible

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

PoroTomo Distributed Temperature Sensing (DTS) Measurements made in Brady Observation Well 56-1

This submission is a follow-up to Distributed Temperature Sensing (DTS) measurements made in Brady observation well 56-1 during the PoroTomo field experiment conducted in March, 2016. The measurements in this data set were made on August 24, 2018 over an approximately 20 hour per...
Kratt, C. et al Oregon State University
Jan 09, 2019
6 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

Brady's Geothermal Field Reftek Seismometer Metadata

Metadata for the Reftek seismometer array deployed at the POROTOMO's Natural Laboratory in Brady Hot Spring, Nevada during the March 2016 testing.
Parker, L. University of Wisconsin
Mar 26, 2016
4 Resources
0 Stars
Publicly accessible

PoroTomo: BRAD and BRDY GPS Station RINEX Files March 26, 2015

This dataset provides links to daily RINEX files for two GPS stations at Brady's Hot Springs as of March 26, 2015. The data is formatted as compressed GNSS RINEX observation files, accessible through formatted CSV files, as well as in links to the complete daily time series data. ...
Kreemer, C. University of Wisconsin
Jan 01, 2015
7 Resources
0 Stars
Curated

PoroTomo: BRAD and BRDY GPS Station RINEX Files December 20, 2014

This dataset provides links to daily RINEX files for two GPS stations at Brady's Hot Springs as of December 20, 2014. The data is formatted as compressed GNSS RINEX observation files and is accessible through CSV files containing metadata such as file size, data type, and publicat...
Kreemer, C. University of Nevada
Dec 20, 2014
4 Resources
0 Stars
Publicly accessible

Analysis of Existing InSAR Data Brady Hot Springs Geothermal Area

Attributes of synthetic aperture radar (SAR) data acquired by TerraSAR-X and TanDEM-X satellite missions and archived at WInSAR facility.
Feigl, K. University of Wisconsin
Dec 26, 2014
1 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

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

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

Bradys Geothermal Field MEQ Relocations 3D Velocity Models

Hypocenters of local microearthquakes and 3D P and S-velocity models computed by simultaneous inversion of arrival times recorded by the Brady seismic network Nov 2010-Mar 2015.
Foxall, W. University of Wisconsin
Jul 01, 2015
4 Resources
0 Stars
Publicly accessible

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
Publicly accessible

GeoThermalCloud framework for fusion of big data and multi-physics models in Nevada and Southwest New Mexico

Our GeoThermalCloud framework is designed to process geothermal datasets using a novel toolbox for unsupervised and physics-informed machine learning called SmartTensors. More information about GeoThermalCloud can be found at the GeoThermalCloud GitHub Repository. More information...
Vesselinov, V. Los Alamos National Laboratory
Mar 29, 2021
4 Resources
0 Stars
Publicly accessible

Brady Geothermal Field Well Lithologies

This dataset provides well lithologies and corresponding descriptions exported from the 3D Leapfrog geologic model of the Brady Geothermal Field in Northwestern Nevada. Two .csv files are included. The file labeled Well Lithologies Descriptions provides the descriptions for each l...
Lopeman, J. University of Wisconsin
Jul 22, 2015
2 Resources
0 Stars
Curated

Training dataset and results for geothermal exploration artificial intelligence, applied to Brady Hot Springs and Desert Peak

The submission includes the labeled datasets, as ESRI Grid files (.gri, .grd) used for training and classification results for our machine leaning model: brady_som_output.gri, brady_som_output.grd, brady_som_output.* desert_som_output.gri, desert_som_output.grd, desert_som_outpu...
Moraga, J. et al Colorado School of Mines
Sep 01, 2020
16 Resources
0 Stars
Curated

Brady's Geothermal Field Sample Interferogram in HDF5 Format

HDF5 file containing phase, filtered phase, unwrapped range change and correlation data for the a TSX pair (Track 53) spanning time interval 12-23-2011 to 10-26-2012.
Ali, T. University of Wisconsin
Jan 01, 2015
1 Resources
0 Stars
Publicly accessible

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

Material Properties for Brady Hot Springs Nevada USA from PoroTomo Project

The PoroTomo team has completed inverse modeling of the three data sets (seismology, geodesy, and hydrology) individually, as described previously. The estimated values of the material properties are registered on a three-dimensional grid with a spacing of 25 meters between nodes....
Feigl, K. and PoroTomo Team, . University of Wisconsin
Mar 06, 2019
10 Resources
0 Stars
Publicly accessible
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