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 - 20 of 20.
Show results per page.
Order by:
Available Now:
Filters Clear All Filters ×
Topic
Technologies
Demonstration Sites
Data Type
"multi-physics"×
Stimulation and Microseismicity×

Utah FORGE 6-3712: Probabilistic Estimation of Seismic Response Using Physics-Informed Recurrent Neural Networks 2024 Annual Workshop Presentation

Sep 17, 2024
52.7 MB
Publicly accessible
This is a presentation on the Probabilistic Estimation of Seismic Response Using Physics-Informed Recurrent Neural Networks by GTC Analytics, presented by Jesse Williams. This video slide presentation discusses the development of machine learning-based predictive tools to estimate...
Authors
Williams, J. Energy and Geoscience Institute at the University of Utah
geothermalenergyutah forgemachine learningmulti frequencystimulation-induced seismicityseismicityseismicity predictorstimulationpredictive systemsdeep learningdlmagnitude-frequency distributionseismicegsvideopresentation

Utah FORGE 6-3712: Probabilistic Estimation of Seismic Response Using Physics-Informed Recurrent Neural Networks 2025 Workshop Presentation

Sep 18, 2025
70.48 MB
Publicly accessible
This is a presentation on the Probabilistic Estimation of Seismic Response Using Physics-Informed Recurrent Neural Networks by GTC Analytics, presented by Dr. Jesse Williams. This video slide presentation discusses the development of machine learning-based predictive tools to esti...
Authors
Williams, J. GTC Analytics
geothermalenergyutah forgeegs2025 annual workshopinduced seismicitymachine learningrecurrent neural networksprobabilistic modelingseismic response predictionmagnitude-frequency analysisphysics-informed aipresentationpresentation recordingpresentation slidesreport

Utah FORGE 6-3712: Report on Building a Recurrent Neural Network Framework for Induced Seismicity October, 2025

Oct 13, 2025
1.62 MB
Publicly accessible
This is a technical report for the Probabilistic Estimation of Seismic Response Using Physics Informed Recurrent Neural Networks project. The report describes the process of designing a recurrent neural network (RNN) to predict induced seismicity. Background material is included t...
Authors
Williams, J. et al Global Technology Connection, Inc.
geothermalenergydeep learninginduced seismicitypredictivemagnitudeartificial intelligenceaimachine learningmldlphysics-basedmodelingutah forgeegstechnical reportseismic datainjection parametersgeophysical modelsprobabilistic

Utah FORGE 6-3712: Report on a Data Foundation for Real-Time Identification of Microseismic Events

Jan 21, 2025
971.63 kB
Publicly accessible
This submission is a technical report for the Probabilistic Estimation of Seismic Response Using Physics Informed Recurrent Neural Networks project. The report describes the process of extracting events from the borehole seismic sensors. To be effective once deployed, the process ...
Authors
Williams, J. et al Global Technology Connection, Inc.
geothermalenergyutah forgedata processingmachine learninginduced seismicitytechnical reportevent detectionmlartificial intelligenceaireal-timephysics informedrecurrent neural networksborehole seismicseismic datamicroseismicevent catalogmagnitude-frequency distributiongeophysicsegs

Utah FORGE 7-3639: Design and Implementation of a Novel Multi-Frac Stimulation Concept 2024 Annual Workshop Presentation

Sep 02, 2024
36.97 MB
Publicly accessible
This is a presentation on the Design and Implementation of a Novel Multi-Frac Stimulation Concept by The University of Oklahoma, presented by Ahmad Ghassemi. This slide presentation video discusses the design and implementation of a reservoir stimulation concept improving near-wel...
Authors
Ghassemi, A. and Jeffery, R. Energy and Geoscience Institute at the University of Utah
geothermalenergyutah forgefracfracingstimulationwell stimulationmulti-fracproppingself-proppinghydraulic fracturesnatural fracturesmulti-stage fracturingegsvideopresentation

Utah FORGE 5-2419: Final Report and Presentation on Seismicity Permeability Relationships Probed via Nonlinear Acoustic Imaging

Sep 30, 2025
254.88 MB
Publicly accessible
This submission contains the final technical report and closeout presentation for Utah FORGE Project 5-2419, which investigates the coupled evolution of permeability and induced seismicity in enhanced geothermal systems using laboratory experiments, field observations, and nonline...
Authors
Elsworth, D. Pennsylvania State University
geothermalenergyutah forgeegspermeabilityinduced seismicitylaboratory experimentsfield observationsnonlinear acoustic imagingfault reactivationreservoir rockmicroearthquakestimulationphysics informed modelingmachine learningseismic momentstress statepermeability creationseismic hazardtechnical reportgeomechanicsgeophysicsmicroseismicity

Utah FORGE: GeoThermOPTIMAL Presentation Video

Dec 12, 2022
20.69 MB
Publicly accessible
This is a project description video by Dr. William W. Fleckenstein related to their "Development of Multi-Stage Fracturing System and Wellbore Tractor to Enable Zonal Isolation During Stimulation and EGS Operations in Horizontal Wellbores" R&D project at Utah FORGE which is linked...
Authors
Fleckenstein, W. Colorado School of Mines
geothermalenergyutah forgeforgemulti-stage fracturingwellbore tractorzonal isolationhorizontal drillingfracturingegsfracingwell stimulationvideoutahdrillingtechnologywellbore technologiessleevesmp4stimulation

QuakeCastNet: Source Code for Forecasting of Injection-Induced Seismicity

Sep 20, 2026
16.21 MB
Curated
This submission houses the companion code for the manuscript by Zhengfa Bi (Lawrence Berkeley National Laboratory) and Nori Nakata (Lawrence Berkeley National Laboratory; MIT). Both the companion code and manuscript are included in the resources section of this submission. Fluid ...
Authors
Nakata, N. and Bi, Z. Lawrence Berkeley National Laboratory
geothermalenergyutah forgeseismicitydeep learningthe geysersforecastegsinduced seismicityseismicity forecastingtftprobabilisticmulti-horizontemporal transformer frameworkmachine learningdecision supporttraffic light

Utah FORGE: Development of Multi-Stage Fracturing System and Wellbore Tractor to Enable Zonal Isolation During Stimulation and EGS Operations in Horizontal Wellbores

Oct 05, 2022
4.59 MB
Publicly accessible
This paper discusses the progress on a project funded by the DOE Utah FORGE (Frontier Observatory for Research in Geothermal Energy) for the development of a subsurface heat exchanger for Enhanced Geothermal Systems (EGS) using unique casing sleeves cemented in place and are used ...
Authors
Fleckenstein, W. et al Colorado School of Mines
geothermalenergycompletionsleevestractorheat modelegsutah forgestimulationfracturingwellbore technologieswellbore technologyheat exchangergeothermoptimalfracoptimal

Utah FORGE 1-2551: Multi-Stage Fracturing System and Well Tractor to Enable Zonal Isolation During Stimulation and EGS Operations in Horizontal Wellbores 2023 Annual Workshop Presentation and Report

Sep 08, 2023
73.57 MB
Publicly accessible
Included here are a presentation recording, slides, and report on the Multi-Stage Fracturing System and Well Tractor to Enable Zonal Isolation During Stimulation and EGS Operations in Horizontal Wellbores project by Colorado School of Mines, presented by Dr. William W. Fleckenstei...
Authors
Fleckenstein, W. et al Colorado School of Mines
geothermalenergyannual workshop2023utah forgeegsstimulationheat-carrier fluidzonal isolationmultistage fracture stimulationinjectionflow controlhorizontal wellborestimulation technologylong-reach injectormulti-stage fracturing systemwell tractorreport

Utah FORGE 6-3712: Curated and Fused 2022 and 2024 Stimulation Injection Datasets and Processing Report February 2026

Feb 25, 2026
155 MB
Publicly accessible
This submission contains curated injection parameter datasets from the 2022 and 2024 stimulation experiments conducted at the Utah FORGE site, along with the report documenting the data processing workflow. The datasets were developed as part of Project 6-3712: Probabilistic Estim...
Authors
Williams, J. et al Global Technology Connection, Inc.
geothermalenergyinduced seismicityinjection parametersdatasetstimulationutah forgeegsstimulation experimentinjection datatreating pressureslurry rateclean ratecumulative injected volumeinflow rateflowbacktime-series dataprocessed datahydraulic stimulationfeomechanics

Utah FORGE 5-2615: Laboratory Data for Insights on Hydraulic Fracture Closure and Stress Measurement

Jun 12, 2024
4.82 MB
Publicly accessible
This dataset includes data from injection/fall-off experiments conducted in controlled laboratory settings. The aim is to investigate the physics governing fracture closure and the associated stress measurements during hydraulic fracturing. These time series data include flow rat...
Authors
Ye, Z. and Ghassemi, A. University of Oklahoma
hydraulic fracturinginjection/fall-off testsin-situ stress measurementsfracture closuregeothermalegsutah forgeminifracstressflow ratepressurevolumelaboratoryenergyinjectionfall-offwater injectionoil injectionsierra white granitecrab orchard sandstonescioto sandstonekismetgeomechanics

EGS Collab Experiment 2: Distributed Fiber Optic Temperature Data (DTS)

Nov 08, 2022
2.77 GB
Publicly accessible
The EGS Collab Experiment took place at the Sanford Underground Research Facility at the Homestake gold mine in Lead, SD, USA. Distributed fiber optic sensing temperature data is included in this dataset for this experiment. A single loop of custom fiber package was grouted into ...
Authors
Rodriguez Tribaldos, V. et al Lawrence Berkeley National Laboratory
geothermalenergyegs collabsurfhydraulicfracturingstimulationsanford underground research facilityexperimentegsdfosfiber opticxt-dtstemperaturedtsexperiment 2distributed sensingmonitoringcharacterization

Utah FORGE 10-3726: Geothermal Multiset Straddle for High Temperature Applications 2024 Annual Workshop Presentation

Sep 17, 2024
32.83 MB
Publicly accessible
This is a presentation on the Geothermal Multiset Straddle (GMS) for High Temperature Applications by Welltec, presented by Ricardo Vasques. This video slide presentation discusses the development of (1) an annular multiset isolation system; (2) a stimulation straddle isolation sy...
Authors
Esquitin, Y. and Vasques, R. Energy and Geoscience Institute at the University of Utah
geothermalenergyutah forgestimulationfracingfracisolation systemopen-close flow systemegsgmsgeothermal multiset straddlevideopresentation

Utah FORGE 1-2410: Development of a Smart Completion and Stimulation Solution 2023 Annual Workshop Presentation

Sep 08, 2023
50.99 MB
Publicly accessible
This is a presentation on the Development of a Smart Completion & Stimulation Solution project by Welltec in collaboration with the University of Oklahoma, presented by Yosafat Esquitin, a Senior Business Development Manager at Welltec. The project's objective was to develop an an...
Authors
Esquitin, Y. et al Welltec
geothermalenergyannual workshop2023utah forgeegsisolation systemannularstimulation isolationstimulationopen-close flow systemzonal isolationzonal stimulationdownhole controlled egsproductive life

Utah FORGE: Well 16A(78)-32 Stage 1 Pressure Falloff Analysis

Aug 04, 2022
1.16 MB
Publicly accessible
This is an analysis of the pressure falloff in stage 1 fracture stimulation of FORGE well 16A(78)-32. The objective of this research is to understand the information content of the well stimulation data of FORGE Well 16A(78)-32. The Stage 1 step-rate test, a variant of the classic...
Authors
Kazemi, H. et al Colorado School of Mines
geothermalenergyutah forgemulti-ratestep-down ratemicro-fracturesmacro-fracturesfracturetracerflowbacktracer flowbackporoelastic propertiesstimulationformation stimulationmicro fracturesmacro fracturespermeabilitytestreportpressure falloffforgeutah

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

EGS Collab Experiment 1: Second Set Tracer Test Results

Dec 19, 2019
4.94 MB
Publicly accessible
The EGS Collab project is developing ~10-20 m-scale field sites where fracture stimulation and flow models can be validated against controlled, small-scale, in-situ experiments. The first multi-well experimental site was established at the 4850 level in the Homestake Mine in Lead,...
Authors
Neupane, G. et al Idaho National Laboratory
geothermalenergyegs collabsurftracer testssigma-vc-dotsrhodamine-bfluoresceinbreakthrough curvechloridetracer datahydraulicfracturingsimulationtracerexperimentalegssanford underground research facilityinjectionsodium chloridelithium bromidecesium iodinetestbed 1stimulation

Final Report: Low Temperature Geothermal Play Fairway Analysis for the Appalachian Basin

Nov 18, 2015
31.13 MB
Publicly accessible
This is a final report summarizing a two-year (2014-16) DOE funded Geothermal Play Fairway Analysis of the Low-Temperature resources of the Appalachian Basin of New York, Pennsylvania and West Virginia. Collaborators included Cornell University, Southern Methodist University, and ...
Authors
E. Jordan, T. Cornell University
geothermalappalachian basinnew yorkpennsylvaniawest virginiadistrict heatingdeep direct uselow-temperaturereservoirproductivityfavorabilityreservoir productivity indexreservoir flow capacitygpfa-abgeothermal play fairway analysisthermal analysisresource assessmentheat flowthermal conductivitygeothermsheat utilizationsurface leveled cost of heatlcohslcohdemandgeophirescombined risk segment mapsrisk analysisinduced seismicityfaultspotential fieldswaveletsbht correctionslow temperature

Newberry EGS Demonstration: Well 55-29 Stimulation Data

Dec 08, 2012
273.53 MB
Publicly accessible
The Newberry Volcano EGS Demonstration in central Oregon, a 3 year project started in 2010, tests recent technological advances designed to reduce the cost of power generated by EGS in a hot, dry well (NWG 55-29) drilled in 2008. First, the stimulation pumps used were designed to ...
Authors
T., T. AltaRock Energy Inc
geothermalegsdiverter materialmicroseismic monitoringtemperature monitoringgroundwater monitoringnewgengeophysical logsdiverter injectionseismicwell constructiondaily reporttracer injection and groundwater monitoringlithologytemperaturegeochemistrystimulation datapublicationswhpflowstimulationhydraulicwaterseismicitymonitoringmicroseismicitywelllogdrillingreportcataloggeophysicscasing55-29diverterstzim
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