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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
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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
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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
0 Stars
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Bradys Hot Springs Ambient Noise Correlation Functions (Initial Waveforms)

These files are ambient noise correlation (ANC) functions calculated for 11 days of continuous seismic data recorded by the Lawrence Berkeley network in the Brady geothermal field. These are SAC formatted seismic waveforms. The stations included are BPB04, BPB05, BPB07, BPB08, BP...

Matzel, E. Lawrence Livermore National Laboratory

Jul 01, 2015
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
10 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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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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Distributed Acoustic Sensing Experiment Data from 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 all DAS data recorded during the experiment. The sampling rate ...

Lancelle, C. University of Wisconsin

Sep 11, 2013
14 Resources
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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
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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