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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
0 Stars
Publicly accessible
1 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
10 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
1 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
1 Resources
0 Stars
Publicly accessible
PoroTomo Project: Brady's Geothermal Field: GPS station deployment and data analysis
Brady's Field PoroTomo project. GPS station deployment and data analysis. Links to data files and website with station and time-series information
Kreemer, C. University of Nevada
Apr 26, 2016
8 Resources
0 Stars
Publicly accessible
8 Resources
0 Stars
Publicly accessible
Guelph, ON Canada DTS Metadata
Metadata for active distributed temperature survey (DTS) experiments at Guelph, Ontario Canada. This data that this metadata refers to was taken as part of the PoroTomo project. The metadata includes information about status, location, elevation, units, and other metadata.
Coleman, T. University of Wisconsin
Dec 15, 2014
3 Resources
0 Stars
Publicly accessible
3 Resources
0 Stars
Publicly accessible
PoroTomo: Horizontal Distributed Acoustic Sensing (DAS) Measurements During an M 2.3 Explosion
Included here are Distributed Acoustic Sensing (DAS) data collected by the horizontal DAS array at Brady's Hot Springs Geothermal Field. The system recorded this data during an M 2.3 explosion at the Nevada Test Site (NTS), which is located approximately 400km southeast of the fie...
Kratt, C. et al Center for Transformative Environmental Monitoring Programs (CTEMPs)
Dec 18, 2018
5 Resources
0 Stars
Curated
5 Resources
0 Stars
Curated
Analyzed Boise Data for Oscillatory Hydraulic Tomography
Data here has been "pre-processed" and "analyzed" from the raw data submitted to the GDR previously (raw data files found at http://gdr.openei.org/submissions/479. doi:10.15121/1176944 after 30 September 2017). First, we submit .mat files which are the "pre-processed" data (must h...
Lim, D. University of Wisconsin
Jul 01, 2015
8 Resources
0 Stars
Publicly accessible
8 Resources
0 Stars
Publicly accessible
PoroTomo Project: Brady's Geothermal Field, Subtask 3.5: GPS Data Analysis
Links to GPS RINEX data not previously reported, plus links to station web pages, which include most up-to-date time-series
Kreemer, C. University of Wisconsin
Jan 04, 2016
7 Resources
0 Stars
Publicly accessible
7 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
Analysis of Existing Data from a Distributed Acoustic Sensing Experiment at Garner Valley, California
In September 2013, an experiment using Distributed Acoustic Sensing (DAS) was conducted at Garner Valley, a test site of the University of California Santa Barbara (Lancelle et al., 2014). This submission includes noise cross-correlation functions (NCF) . Each file includes a NCF ...
Zeng, X. University of Wisconsin
Mar 26, 2015
37 Resources
0 Stars
Publicly accessible
37 Resources
0 Stars
Publicly accessible