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Brady's, NV×

Material Properties for Brady Hot Springs Nevada USA from PoroTomo Project

Mar 06, 2019
242.91 MB
Publicly accessible
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....
Authors
Feigl, K. and PoroTomo Team, . University of Wisconsin
geothermalenergyporotomoseismologygeodesyhydrologynevadabrady hot springsporoelastic tomographyinversionmodeling3dmaterialpropertiesunconsolidatedfracturedshallowstructuraltrendsgeologystrikedipthermal contractionpressuresubsidencepumpinghydraulic conductivityrateseismic amplitudefaultzonepermeableconduitfluidreservoirconceptualmodelpropertydensityp-waves-waveseismicvelocityyoungs moduluspoissons ratiointerferometrytemperaturelithologystrain rate

Understanding Constraints on Geothermal Sustainability Through Reservoir Characterization at Brady Geothermal Field, Nevada

Jul 11, 2018
4.46 MB
Publicly accessible
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 ...
Authors
Patterson, J. University of Wisconsin
geothermalenergyhydrogeologydtsreservoir characterizationnevadabrady hot springsborehole pressureborehole temperaturedistributed temperature sensingporotomosustainabilitysustainable usesubsurface propertiesresorceidentificationassessmentproductioncharacterizationtemperaturepressurethermalhydraulicpropertiesanalyticalmodelnumericalanalysisreservoirsensitivityflow pathsfracturesflowpathwayspreferentialheattransportparameterssimulationpower production

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

3-D Geologic Controls of Hydrothermal Fluid Flow at Brady Geothermal Field, Nevada using PCA

Oct 01, 2021
7.12 MB
Publicly accessible
In many hydrothermal systems, fracture permeability along faults provides pathways for groundwater to transport heat from depth. Faulting generates a range of deformation styles that cross-cut heterogeneous geology, resulting in complex patterns of permeability, porosity, and hydr...
Authors
Siler, D. and Pepin, J. United States Geological Survey
geothermalenergypca3d geologic modelgeologic modelgeologycharacterizationmachine learningmlbhsbrady hot springsprincipal component analysisproductionstressfaultsrbradyhydrothermalgeologic structureunsupervised3d well datacodegeothermicgeophysics

Raw Pressure Data from Observation Wells at Brady's Hot Springs

Mar 13, 2016
5.15 MB
Publicly accessible
This .csv files contain the raw water pressure data from three observation wells during pumping tests performed in the Spring of 2016. Included is a "read me" file explaining the details of where and how the data were collected.
Authors
Lim, D. University of Wisconsin
geothermalpressure sensorpressurebrady hot springsobservation wellspumping testspressure datawater pressureread me fileobservation wellporotomobradys geothermal area

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

Brady Geodatabase for Geothermal Exploration Artificial Intelligence

Apr 27, 2021
179.02 GB
Publicly accessible
These files contain the geodatabases related to Brady's Geothermal Field. It includes all input and output files for the Geothermal Exploration Artificial Intelligence. Input and output files are sorted into three categories: raw data, pre-processed data, and analysis (post-proces...
Authors
Moraga, J. et al Colorado School of Mines
geothermalenergygeodatabasebrady hot springsbradyartificial intelligenceaibrady wellseismicremote sensinghyperspectralgeospatial databasedeep learningmachine learningexplorationsite detectiongeothermal site detectionanomaly detectionshort wavelength infraredswirsupport vector machinesvmland surface temperaturelstwellraw dataprocessed datanevadaarcgismodeldatabasehydrothermalgeophysicsradargisblindblind systemdeformationgeophysicalhyperspectral imagingconceptual modelfaultpreprocessedrastervectorfield datageospatial data

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