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Brady's Geothermal Field Metadata for DTS and DAS Surveys

Metadata for DTS and DAS datasets for both borehole 56-1 and trenched cables.

Coleman, T. University of Wisconsin

Mar 26, 2016
5 Resources
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Brady's Geothermal Field Distributed Temperature Sensing Data

This submission is an 8 day time history of vertical temperature measurements in Brady observation well 56-1 collected during the PoroTomo field experiment. The data was collected with a fiber-optic DTS system installed to a depth of 372 m below wellhead. DTS installation uses a d...

Patterson, J. University of Wisconsin

Mar 26, 2016
2 Resources
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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
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Brady's Geothermal Field DTS Raw Data

The submitted data correspond to the complete raw temperature datasets captured by the distributed temperature sensing (DTS) horizontal and vertical arrays during the PoroTomo Experiment. Files in each submitted resource include: .xml (level 0): Data that includes Stokes, Anti-S...

Coleman, T. University of Wisconsin

Mar 26, 2016
4 Resources
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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

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
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Brady's Geothermal Field DAS Vibroseis Data

The submitted data correspond to the monitored vibrations caused by a vibroseis seismically exciting the ground in the vertical direction and captured by the DAS horizontal and vertical arrays during the PoroTomo Experiment. The data also include a file with the acceleration recor...

Feigl, K. University of Wisconsin

Mar 25, 2016
11 Resources
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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
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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
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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
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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
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