OpenEI: Energy Information
  • Geothermal Data Repository
  • My User
    • Sign Up
    • Login
 
  • Data
    • View All Submissions
    • Data Lakes
    • Data Standards
    • Submit Data
  • Help
    • Frequently Asked Questions
    • Data Submission Best Practices
    • Data Submission Tutorial Videos
    • Contact GDR Help
  • About
  • Search

Search GDR Data

Showing results 1 - 25 of 1451.
Show results per page.
Order by:
Available Now:
Filters
Topic
Technologies
Demonstration Sites
Data Type

Utah FORGE: Seismic Velocity Models, February 2021

Feb 28, 2021
10.92 MB
Publicly accessible
This dataset contains a map, showing the Utah FORGE seismic stations, and seismic velocity model data. There are 61 1-D velocity models which are in a compressed TAR file. A paper is referenced at the end of this description which discusses the use of these data in 3D modelling. T...
Authors
Pankow, K. Energy and Geoscience Institute at the University of Utah
geothermalenergyseismic data1d seismic velocityseismic velocityutah forgeforgeutah geothermalvelocity modelsseismicvelocityspacspatial auto-correlationpseudo-3dgeophonebayesian monte carlo inversionmodelingmodeldistributed acoustic sensinggeospatial datasedimentary basinwaveform inversionseismic noisegeophysicstaregsroosevelt hot springsutahmilford

Utah FORGE: Well 16A(78)-32: Summary of Drilling Activities

Mar 20, 2021
10.48 MB
Publicly accessible
This is a 74 page detailed summary of the drilling activities of Utah FORGE 16A(78)-32, a highly deviated well completed on February 2nd, 2021, as part of the Utah FORGE project. This well was deviated at 65 degrees from vertical after reaching 6000 feet in depth had a total measu...
Authors
Winkler, D. et al Energy and Geoscience Institute at the University of Utah
geothermalenergywell 16a78-32utah forgeforgeutah geothermaldeviated well 16a78-32deviated wellsegs16a78-32well datadrillingwell logcharacterizationdrill stem testroosevelt hot springsmilford

GeoThermalCloud framework for fusion of big data and multi-physics models in Nevada and Southwest New Mexico

Mar 29, 2021
179.87 MB
Publicly accessible
Our GeoThermalCloud framework is designed to process geothermal datasets using a novel toolbox for unsupervised and physics-informed machine learning called SmartTensors. More information about GeoThermalCloud can be found at the GeoThermalCloud GitHub Repository. More information...
Authors
Vesselinov, V. Los Alamos National Laboratory
geothermalenergymachine-learningnew mexicobradynevadagreat basinsouthwest new mexicomulti-physicsbrady hot springssmarttensorsgeothermalcloudgeothermal cloudlos alamos national laboratorysite datasimulationmachine learningmodel

GEOPHIRES files for DDU techno-economic simulations

Mar 31, 2021
652.14 kB
Publicly accessible
During 2017-2019, the U.S. Department of Energy funded six geothermal deep direct-use (DDU) projects to investigate feasibility of DDU for heating, cooling and thermal storage in the United States. In a follow-on study conducted at the National Renewable Energy Laboratory (NREL), ...
Authors
Beckers, K. and Kolker, A. National Renewable Energy Laboratory
geothermalenergygeophiresdeep direct-useddueconomicstechno-economicsimulationmodelheatingcoolingenergy storagedeep direct usepythonnrelsandiacornellfeasibilitycostfinancingdefaultdgeo ti

Utah FORGE: Well 58-32 (MU-ESW1) FMI Log Fracture Results

Mar 06, 2021
4.55 kB
Publicly accessible
A Schlumberger Fullbore Formation Micro-Imager (FMI) log was run from 7390 feet to 7527 feet depth in well 58-32, originally known as well MU-ESW1. Well 58-32 was completed in 2017 as part of Utah FORGE Phase 2. It reached a depth of 7536 feet and recorded a bottom hole temperatur...
Authors
BLOCHOWICZ, A. Energy and Geoscience Institute at the University of Utah
geothermalenergyschlumberger fmifmi logutah forgeutah geothermalwell 58-32mu-esw1well 58-32 logschlumbergerfullboreformation microimagerfmiwell loglogginglogsfractureegswell 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

EGS Collab Experiment 1: Circulation Testing Processed data

Apr 01, 2021
129.85 MB
Publicly accessible
This submission includes processed and reduced data for circulation testing that was conducted at the 164' fracture on the 4850 ft level of the Sanford Underground Research Facility. The circulation tests were done to test the flow through the 164' fracture in the EGS Collab Exper...
Authors
Fu, P. et al Lawrence Livermore National Laboratory
geothermalenergyegs collabsurfsanford underground research facilityexperimentegscirculationthermal drawdownprocessed datadata processingpythoncodeinjection testinjection rateinjection pressureflowpressuretemperaturestimulation

Directional Cooling-Induced Fracturing Westerly Granite Test Results

Dec 18, 2020
72.48 MB
Publicly accessible
Directional Cooling-Induced Fracturing (DCIF) experiments were conducted on a short, cylindrical sample of Westerly granite (diameter = 4 inches, height ~ 2 inches). Liquid nitrogen was poured in a copper cup attached to the top of the sample, and the resulting acoustic emissions ...
Authors
Nakagawa, S. Lawrence Berkeley National Laboratory
geothermalthermal crackingacoustic emissionstemperature changeslaboratory experimentwesterly granitegranitemoment tensorfractureseismicgeophysicsliquid nitrogenthermaltemperaturestimulationdirectional coolinginduced fracturingdirectional cooling-induced fracturingwellborestressvelocitytomographymicrocracking

Appendices for Geothermal Exploration Artificial Intelligence Report

Jan 08, 2021
2.76 GB
Publicly accessible
The Geothermal Exploration Artificial Intelligence looks to use machine learning to spot geothermal identifiers from land maps. This is done to remotely detect geothermal sites for the purpose of energy uses. Such uses include enhanced geothermal system (EGS) applications, especia...
Authors
Duzgun, H. et al Colorado School of Mines
geothermalenergyartificial intelligencehydrothermally altered mineralsmineral markerssvmgeodatabasewellfaultseismicaiborderbradydesert peaksalton sealand surface temperaturedeformationgeophysicalgeophysicssupport vector machinehyperspectralhyperspectral imagingcalifornianevadaegsblindblind systemdeep learningmachine learningexplorationgeospatial datashort wavelength infraredswirdatabaseanomaly detectionsite detectionradarhydrothermalmodelconceptual modelzoteroraw datapreproccessedprocessed dataenhanced geothermal systemengineered geothermal systemremote sensingarcgisgisinsarmorphologymorphologicalmorphological featurestirvnirvisible near infraredthermal infraredcodepython

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

Desert Peak Geodatabase for Geothermal Exploration Artificial Intelligence

Apr 27, 2021
59.5 GB
Publicly accessible
These files contain the geodatabases related to the Desert Peak Geothermal Field. It includes all input and output files used in the project. The files include data categories of raw data, pre-processed data, and analysis (post-processed data). In each of these categories there ar...
Authors
Moraga, J. et al Colorado School of Mines
geothermalenergygeodatabasenevadadesert peakartificial intelligenceairaw dataprocessed dataremote sensinghyperspectralmachine learningdeep learningexplorationarcgismodelsite detectionanomaly detectiongeothermal site detectiondatabasehydrothermalgeophysicsradarshort wavelength infraredswirsupport vector machinesvmland surface temperaturelstwellgisblindblind systemhyperspectral imaginggeophysicaldeformationconceptual modelfaultpreprocessedgeospatial data

Salton Sea Geodatabase for Geothermal Exploration Artificial Intelligence

Apr 27, 2021
148.82 GB
Publicly accessible
These files contain the geodatabases related to Salton Sea Geothermal Field. It includes all input and output files used with the Geothermal Exploration Artificial Intelligence. Input and output files are sorted into three categories: raw data, pre-processed data, and analysis (po...
Authors
Moraga, J. et al Colorado School of Mines
geothermalenergygeodatabasesalton seaartificial intelligenceaideep learningmachine learningseismicremote sensinghyperspectralhyperspectral imaginggeospacial databaseexplorationsite detectiongeothermal site detectionanomaly detectionshort wavelength infraredswirsupport vector machinesvmland surface temperaturelstwellraw dataprocessed datacaliforniaarcgisgismodeldatabasehydrothermalgeophysicsradarblindblind systemdeformationgeophysicalconceptual model faultpreprocessedrastervectorfield datageospatial data

Programs and Code for Geothermal Exploration Artificial Intelligence

Apr 27, 2021
710.72 kB
Publicly accessible
The scripts below are used to run the Geothermal Exploration Artificial Intelligence developed within the "Detection of Potential Geothermal Exploration Sites from Hyperspectral Images via Deep Learning" project. It includes all scripts for pre-processing and processing, including...
Authors
Moraga, J. Colorado School of Mines
geothermalenergycodershell scriptsgeothermal aimachine learningself organizing mapk-meanspythonaiartificial intelligencedeep learningexplorationgeothermal explorationremote sensingblindsite detectionlstland surface temperaturenumpyrastertensorflowk meananomaly detectionlandsat adr lstsbatchslurmshell

Sentinel-1 Input Data for PSInSAR Analysis

Apr 29, 2021
305.43 GB
Publicly accessible
Files used to perform the Persistent Scatterer InSAR analysis with SARPROZ. The data is sourced from ESAs Sentinel-1 project and covers Brady Hot Springs and Desert Peak geothermal areas. The original titles are included for the Sentinel-1 data. The naming guide is included as a l...
Authors
Moraga, J. Colorado School of Mines
geothermalenergyinsarpsinsarsentinel-1synthetic aperture radarsatellite imagingaiartificial intelligencedeep learningmachine learningaerial photographyremote sensingsite detectionanomaly detectioninput datageologydisplacementsubsoilphenomenaprocessed dataradarimaginginterferometricanalysissoil deformationgeospatial data

Active Source Seismic (Ultrasonic) Data from Double-Direct Shear Lab Experiments

May 05, 2021
Size unavailable
Publicly accessible
Active source ultrasonic data from lab experiments p5270 and p5271 including raw waveforms (WF) and mechanical data (mat). From the PSU team working on the "Machine Learning Approaches to Predicting Induced Seismicity and Imaging Geothermal Reservoir Properties" project. The fric...
Authors
Marone, C. Pennsylvania State University
geothermalenergyseismicactive sourcelaboratoryfriction experimentultrasonicgeophysicsmicroseismicitylab dataraw datawaveformsmechanical datapreprocessedmatlabacousticsacousticbiaxial testing apparatusultrasonic acoustic monitoring systemmachine learningdeep learningaiartificial intelligenceseismic forecastingearthquake forecastingfault

Data Arrays for Microearthquake (MEQ) Monitoring using Deep Learning for the Newberry EGS Sites

May 05, 2021
11.59 GB
Publicly accessible
The 'Machine Learning Approaches to Predicting Induced Seismicity and Imaging Geothermal Reservoir Properties' project looks to apply machine learning (ML) methods to Microearthquake (MEQ) data for imaging geothermal reservoir properties and forecasting seismic events, in order to...
Authors
Zhu, T. Pennsylvania State University
geothermalenergycodedeep learningmachine learningaiartificial intelligenceegsenhanced geothermal systemsengineered geothermal systemsnewberryoregonnewberry volcanomlraw dataprocessed datamicroseismicitynumpywaveformpreprocessedpythonnewberry volcanic sitemicroearthquakemeqseismicgeophysicsgeophysical

Hybrid machine learning model to predict 3D in-situ permeability evolution

Nov 22, 2022
5.58 MB
Publicly accessible
Enhanced geothermal systems (EGS) can provide a sustainable and renewable solution to the new energy transition. Its potential relies on the ability to create a reservoir and to accurately evaluate its evolving hydraulic properties to predict fluid flow and estimate ultimate therm...
Authors
Elsworth, D. and Marone, C. Pennsylvania State University
geothermalenergyegsnewberryhydraulicstimulationprocessed datamachine learningpermeability evolutionhydraulic fracturinginduced seismicityegs collabseismic data analysiswellhead pressureflow ratefracture permeabilitymicroearthquakeenhanced geothermal systems

Processed Lab Data for Neural Network-Based Shear Stress Level Prediction

May 14, 2021
6.01 MB
Publicly accessible
Machine learning can be used to predict fault properties such as shear stress, friction, and time to failure using continuous records of fault zone acoustic emissions. The files are extracted features and labels from lab data (experiment p4679). The features are extracted with a n...
Authors
Marone, C. et al Pennsylvania State University
geothermalenergymatlabgeophysicsseismiccodeprocessed datamicroseismicityaiartificial intelligencedeep learningmachine learningacousticsacoustic emissionsseismic forcastingseismic predictionfaultfault propertiesshear stresstime to failureexperimentexperimental datalab databiaxial shear experimentbiaxial shear apparatusfriction

Geothermal Mineral Alterations in Brady and Desert Peak

May 15, 2021
1.54 GB
Publicly accessible
Results of the analysis of HyMap's spectra against know hydrothermally altered minerals in the Brady-Desert Peak Geothermal Areas. This is the post-processing results and final analysis results of applying target detection algorithms and then fusing the results.
Authors
Moraga, J. Colorado School of Mines
geothermalenergymineral alterationshydrothermal alteration mineralshymapbradydesert peakgeospatial datadataprocess dataremote sensingtarget detectionspectral analysisgeothermal areanevada

Utah FORGE: Phase Native State FALCON Model Files

Jun 06, 2019
11.78 MB
Publicly accessible
The submission includes FALCON input file and mesh for the an initial pressure-temperature simulation, and a second set for pressure-temperature-displacement simulation. All simulations are steady state. Data and input for the FORGE Phase 2 native state model were compiled from hi...
Authors
Podgorney, R. Idaho National Laboratory
geothermalenergyfalconforgenative stateutahroosevelt hot springsmilfordegsenhanced geothermal systemengineered geothermal systemutah forgecodesimulationscprocessed datapreprocessed dataraw datageospatial data3-d modellinggeologytemperaturestresspressurecharacterizationmodeling3-d modelinglithologymesh fileinputslithologic contacts

Play Fairway Analysis of the Snake River Plain, Idaho: Final Report

Feb 19, 2021
74.24 MB
Publicly accessible
This submission includes the final project report of the Snake River Plain Play Fairway Analysis project as well as a separate appendix for the final report. The final report outlines the application of Play Fairway Analysis (PFA) to geothermal exploration, specifically within the...
Authors
Shervais, J. et al Utah State University
geothermalenergysrppfasnake river plainidahoblindresourcecharacterizationgeologyblind resourcesblind systemswestern snake river plaincentral snake river plaingeophysicsgravitymagneticsseismictemperaturegeothermometrygeochemistryaqueoustrace elementsisotoperadiometrywellarcgispythoncommon risk segment mappingcrsccrsgeochemicalmagnetotelluricsmtconceptual modelgisthermal modelinghydrothermalintegrated modelintegrated geohydrological modelgeology mapengineered geothermal systemegsmapdrillingwater chemistrypetrographyplay fairway analysisalgorithm

Utah FORGE: Well 16A(78)-32 Simplified Discrete Fracture Network Data

Jun 01, 2021
525.86 MB
Publicly accessible
The FORGE team is making these fracture models available to researchers wanting a set of natural fractures in the FORGE reservoir for use in their own modeling work. They have been used to predict stimulation distances during hydraulic stimulation at the open toe section of well 1...
Authors
Finnila, A. Golder Associates Inc.
geothermalenergyutah forgeforgeutah geothermalreservoirengineeringhydraulicfracturingegsdfndiscrete fracture networkwell 16a78-32utahenhanced geothermal systemengineered geothermal systemfracmanroosevelt hot springsroosevelt hot springs geothermal sitemilfordprocessed datacsvwelldrillingstimulationpressuremodelmodeling

Utah FORGE: UGS Interactive Geoscience Map

Jan 01, 2021
Size unavailable
Publicly accessible
This is a link to the Utah Geological Survey's Utah FORGE Interactive Geoscience Map. The map layers include information on geology, geography, subsurface temperatures, seismicity, gravity and groundwater. Instructions for using the interactive map and a legend for the interactive...
Authors
Hill, J. Utah Geological Survey
geothermalenergyutah forgeinteractive mapgeology mapgravity maptemperature mapseismicity mapgroundwater mapugs mapsutah geological survey mapsutah forge mapsmapgeologyseismiclstgroundwaterhydrologyugsutahforgeinteractivegravityprocessed datageospatial datawater table depthgroundwater chemistrywellfaultwell temperaturetemperaturebedrockbedrock surfacebeddingfoliationcontactgeographycharcterizationegsmilfordroosevelt hot springsenhance geothermal systemengineered geothermal system

Utah FORGE: Induced Seismicity Mitigation Plan

Dec 30, 2020
13.29 MB
Publicly accessible
This is the current induced seismicity mitigation plan (ISMP) for the Utah FORGE project. Information that was collected during Phases 1 and 2 of the Utah FORGE project has been incorporated, as have literature searches and risk assessments. The purpose of this report is to identi...
Authors
Utah, U. et al Energy and Geoscience Institute at the University of Utah
geothermalenergyseismicityinduced seismicityseismicity mitigationutah forgeinduced seismicity mitigation planearthquakesseismicrisk mitigationriskhazardmitigationearthquakeutahmitigation planplangeophysicsegsfaultfaults

Utah FORGE: Seismic Stations and Wells GPS Survey Data, 2021

Jun 30, 2021
3.52 kB
Publicly accessible
This is a CSV spreadsheet containing UTM and Latitude and Longitude coordinates and elevations for Wells 78-32, 58-32, and 16A(78)-32 and BOR1, BOR2, BOR3, FOR2, FOR5, FORK, FORU, and FORW seismic stations. These are from a GPS survey conducted by the Utah Geological Survey in Jun...
Authors
Erickson, B. Utah Geological Survey
geothermalenergyutah forge wells coordinatesutah forge seismic station coordinatesutah forge wells elevationsutah forge seismic stations elevationsutah forgeutah forge gps surveyutahwellgpsseismicelevationsutah geological surveystationcoordinatesseismicitygeophysicsgeophysicalutm
12345Next >>
Google Map
  • About the GDR
  • Partners & Sponsors
  • Disclaimers
  • Developer Services
  • The GDR provides free access to data generated from projects funded by the U.S. Department of Energy's Office of Geothermal.
  • Content is available under Creative Commons Attribution 4.0 unless otherwise noted.

Privacy Policy Notification

This site uses cookies to store and share user preferences with other OpenEI sites, and uses Google Analytics to collect anonymous user information such as which pages are visited, for how often, and what searches or other webpages may have led users here. You can prevent Google Analytics from recognizing you on return visits to this site by disabling cookies on your browser or by installing a Google Analytics Opt-out Browser Add-on. By clicking "Accept" you agree this site can store cookies on your device and disclose information to OpenEI and Google Analytics in accordance with our privacy policy.

OpenEI Privacy Policy Google Analytics Terms of Service