Search GDR Data

Showing results 1 - 3 of 3.
Show results per page.
Order by:
Available Now:
Clear All Filters ×
Topic
Technologies
Demonstration Sites
Data Type
"strain change"×
Hydrothermal×

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

Jun 27, 2018
4.98 GB
Publicly accessible
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...
Authors
Reinisch, E. et al University of Wisconsin
geothermaldashporotomoslow strainbrady hot springsdashorizontaldistributed acoustic sensingmatlabstrain ratestraincharacterizationgeophysicshydrothermalbradyprocessed datasoftwarerepositorytechnicalreportslow strain rate

Envisat Track 349 and Sentinel-1A Track 64 Interferometric Synthetic Aperture Radar Data of Coso Geothermal Field, California, USA, 2004-2016

Jun 25, 2019
648.26 MB
Publicly accessible
This submission contains tarred pair directories for interferometric synthetic aperture radar (InSAR) data covering Coso Geothermal Field in California, USA. Explanation of pair subdirectories: Pairs are formed using the InSAR processing software GMT5SAR (Sandwell et al., 2011). ...
Authors
Reinisch, E. and Feigl, K. University of Wisconsin
geothermalenergyinsardemcoso geothermal fieldcaliforniaenvienvisats1asentinel-1aremote sensingcosotrack 349track 64pairgmt5sardigital elevation modelraw dataprocessed datageospatial dataphaseporotomocharacterizationhydrothermalhigh temperatureradar

Publications and Datasets from Play-Fairway Retrospective Analysis with Emphasis on Developing Improved Hydrothermal Energy Assessments

Feb 07, 2023
Size unavailable
Publicly accessible
Previous moderate and high-temperature geothermal resource assessments of the western United States utilized data-driven methods and expert decisions to estimate resource favorability. Although expert decisions can add confidence to the modeling process by ensuring reasonable mode...
Authors
Mordensky, S. et al United States Geological Survey
geothermalenergypfahydrothermalenergy assessmentresource assessmentretrospectivemachine learninggeosciencewestern usdata-drivenbias reductionfavorabilitymappingegslow tempprocessed dataresourcecharacterization