Search GDR Data

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

Garner Valley DAS Metadata

Metadata for the data collected at the NEES@UCSB Garner Valley Downhole Array field site on September 10-12, 2013 as part of the larger PoroTomo project.

Lancelle, C. University of Wisconsin

Sep 10, 2013
1 Resources
0 Stars
Publicly accessible

Brady's Geothermal Field Seismic Network Metadata

Brady's geothermal field seismic network station locations and dates of operation.

Foxall, W. University of Wisconsin

Dec 21, 2014
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

Brady's Field GPS Time-Series Data

Daily position time-series for GPS station BRAD and BRDY in the NA12 reference frame.

Kreemer, C. University of Nevada

Dec 20, 2014
1 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

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

Brady Geothermal Field Well Pumping Data During Deployment

Contains pumping data associated with the wells used in the 2016 Spring Campaign led partially by UW Madison, LBNL, and LLNL scientists. The well coordinates and the depths to the pressure sensors used in the pumping wells can be found at the link "Coordinates and Sensor Depths" b...

Feigl, K. University of Wisconsin

Mar 30, 2016
3 Resources
0 Stars
Publicly accessible

Brady's Field GPS RINEX Files 12-20-2014

CSV files with links to individual GPS RINEX files.

Kreemer, C. University of Nevada

Dec 20, 2014
4 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

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

Graph Theory for Analyzing Pair-wise Data: Application to Interferometric Synthetic Aperture Radar Data

Graph theory is useful for estimating time-dependent model parameters via weighted least-squares using interferometric synthetic aperture radar (InSAR) data. Plotting acquisition dates (epochs) as vertices and pair-wise interferometric combinations as edges defines an incidence gr...

Reinisch, E. University of Wisconsin

Jul 28, 2016
1 Resources
0 Stars
Publicly accessible

Porotomo: InSAR Data from San Emidio Geothermal Field, Nevada, 1992-2010

This submission contains tarred pair directories for interferometric synthetic aperture radar (InSAR) data covering San Emidio Geothermal Field in Nevada, USA as part of the porotomo project. Data included within this submission are the following: > ENVI_T120_GDR.tgz: Tarred direc...

Reinisch, E. and Feigl, K. University of Wisconsin

Jun 25, 2019
7 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

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
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