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"CO2 injection"×
Brady's, NV×

Brady Hot Springs Seismic Modeling Data for Push-Pull Project

Jul 31, 2018
16.99 GB
Publicly accessible
This submission includes synthetic seismic modeling data for the Push-Pull project at Brady Hot Springs, NV. The synthetic seismic is all generated by finite-difference method regarding different fracture and rock properties.
Authors
Zhang, R. University of Louisiana
geothermalenergyseismicgeophysicsactive sourcevelocitygeophysicaldatamodelingnumericalsyntheticbrady hot springsnevadanvfracturerockgeologicpropertiespropertypush-pullfinite differencenumerical modelingvspvertical seismic profilingboreholefracturednon-fracturedmediaco2saturation

Nevada Production and Injection Well Data for Facilities with Flash Steam Plants

Jan 01, 2009
881.6 kB
Publicly accessible
Files contain a summary of the production and injection data submitted by the geothermal operators to the Nevada Bureau of Mines and Geology over the period from 1985 thru 2009
Authors
Mines, G. Idaho National Laboratory
geothermalbeowaweproduction datainjection databrady hot springsdesert peakdixie valleysteamboat hillsproducitoninjection

Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs

Feb 18, 2021
4.49 MB
Publicly accessible
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...
Authors
Beckers, K. et al National Renewable Energy Laboratory
geothermalenergymachine learningsubsurfacecharacterizationbrady hot springspredictionreservoir modelingtime seriespcaprincipal component analysisreservoir managementbradys hot springsporotomoreservoirdual-porositystimulationinjection testmodeltemperatureflowpressuresimulationsingle-fracturedoubletheatmapheat maptensorflow

Active Source 3D Seismic Tomography of Brady Hot Springs Geothermal Field, Nevada

Aug 09, 2017
26.79 MB
Publicly accessible
We deployed a dense seismic array to image the shallow structure in the injection area of the Brady Hot Springs geothermal site in Nevada. The array was composed of 238 5 Hz, three-component nodal instruments and 8,700 m of distributed acoustic sensing (DAS) fiber-optic cable inst...
Authors
Parker, L. University of Wisconsin
geothermalbrady hot springsnevadaseismic tomographyactive sourceporotomobrady geothermal fieldbradysshallowseismic imagingporoelastic tomography

Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs Results

Oct 20, 2021
6.41 MB
Publicly accessible
Geothermal power plants typically show decreasing heat and power production rates over time. Mitigation strategies include optimizing the management of existing wells increasing or decreasing the fluid flow rates across the wells and drilling new wells at appropriate locations. Th...
Authors
Beckers, K. et al National Renewable Energy Laboratory
geothermalenergymachine learningmlsubsurfacecharacterizationbrady hot springsbhspredictionreservoir modelingtime seriespcaprincipal component analysisreservoir managementreservoirdual-porositystimulationinjection testpdetemperatureflowpressuresimulationsingle-fracturedoubletheat maptensorflowcnnlstmmlphydrothermalopen source reservoirosrnevada

Brady's Geothermal Field Analysis of Pressure Data

Mar 17, 2017
10.13 MB
Publicly accessible
*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 ...
Authors
Lim, D. University of Wisconsin
geothermalenergyproduction flow rate datainjection flow rate datapressure datahydrologyhydrogeologybrady hot springsporotomoporoelastic tomographyegsenhanced geothermal systemsengineered geothermal systemsdeployment databradybradys geothermal fieldpressureflow rateboreholedownholewell datapressure sensorobservation wellspumping testwater pressureobservation well

Machine Learning to Identify Geologic Factors Associated with Production in Geothermal Fields: A Case-Study Using 3D Geologic Data from Brady Geothermal Field and NMFk

Oct 01, 2021
5.68 MB
Publicly accessible
In this paper, we present an analysis using unsupervised machine learning (ML) to identify the key geologic factors that contribute to the geothermal production in Brady geothermal field. Brady is a hydrothermal system in northwestern Nevada that supports both electricity producti...
Authors
Siler, D. et al United States Geological Survey
geothermalenergynmfkbrady hot springsmachine learningmlbhsnonnegative matrix factorization k-meanshydrothermalbradyk-meansclusteringnonnegative matrix factorizationmatrix factorizationgeothermalcloudsmarttensorsunsupervised3d well data3d geologic mapgeologic structurefaultsstressgeologycharacterizationgeologic modelproductioncode