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 - 15 of 15.
Show results per page.
Order by:
Available Now:
Filters Clear All Filters ×
Topic
Technologies
Demonstration Sites
Data Type
"cross-correlation"×
Stimulation and Microseismicity×

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

Effective Elastic and Neutron Capture Cross Section Calculations Corresponding to Simulated Fluid Properties from CO2 Push-Pull Simulations

Mar 07, 2018
4.46 MB
Publicly accessible
The submission contains a .xls files consisting of 10 excel sheets, which contain combined list of pressure, saturation, salinity, temperature profiles from the simulation of CO2 push-pull using Brady reservoir model and the corresponding effective compressional and shear velocity...
Authors
Chugunov, N. and Altundas, B. Lawrence Berkeley National Laboratory
geothermalenergyco2carbon dioxidepush-pullactive seismicwell loggingegsneutron capturesnuparstimulationsensitivity analysischaracterizationfaultfracturefluidbrine

EGS Collab Experiment 1: Baseline Cross-well Seismic

Apr 30, 2018
2.13 GB
Publicly accessible
As part of the geophysical characterization suite for the first EGS Collab tesbed, here are the baseline cross-well seismic data and resultant models. The campaign seismic data have been organized, concatenated with geometry and compressional (P-) & and shear (S-) wave picks, and ...
Authors
Schwering, P. et al Sandia National Laboratories
geothermalenergygeophysicsseismiccross-wellsgysegymodeldataresultsvelocityp-waves-waveelastic modulivisualizationcalculationinversionhydrofractureexperimentsurfsanford underground research facilityegsenhanced geothermal systemcollabboreholebaselinedensityshearbulkyoungsmodulusmodulistimulationhydraulicegs collab

Utah FORGE: Well 16B(78)-32 Extended Dual Well Circulation Testing Fiber Optic Monitoring Report August 2024

Aug 30, 2024
10.95 MB
Publicly accessible
This report documents the post-hydraulic fracturing extended circulation test between Utah FORGE wells 16A and 16B conducted in August 2024. In well 16B, fiber optic measurements of Rayleigh frequency shift distributed strain sensing (RFS-DSS) and distributed temperature sensing ...
Authors
Jurick, D. et al Neubrex Energy Services (US), LLC
geothermalenergycirculation testscross well circulationfiber opticsrfs dssdtsstrain changethermal sluggingthermal strainpltproduction logging toolutah forgeegsstimulaitonhydraulic fracturingdssdistributed temperature sensingdistributed strain sensingfiber optic monitoringprocessed datatechnical reportneubrexgeophysics16b78-32

Utah FORGE: 16B(78)-32 RFS DSS Strain Change Rate and Selected FDIs During 16A(78)-32 Stimulation

Mar 02, 2025
2.11 MB
Publicly accessible
This dataset contains strain change rate versus depth data acquired using a Rayleigh frequency shift (RFS) distributed strain sensing (DSS) system during hydraulic stimulation of well 16A(78)-32 at the Utah FORGE site in April 2024. The data were collected from an optical fiber in...
Authors
Jurick, D. et al Neubrex Energy Services (US), LLC
geothermalenergyutah forgeneubrexstrain frac logfiber opticsmicrostrainstraincumulative strain change ratestrain change16a78-3216b78-32egshydraulic stimulationfiber optic sensingstrain change raterfsdssrayleigh frequency shiftdepth profileprocessed datafrac loggeomechanicsfracture driven interactionsfdifrac hitsperforation clustercross-well strain monitoring

Utah FORGE 4-2541: Optimization and Validation of a Plug-and-Perf Stimulation Treatment Design 2023 Annual Workshop Presentation

Sep 08, 2023
62.84 MB
Publicly accessible
This is a presentation on the Optimization and Validation of a Plug-and-Perf Stimulation Treatment Design at Utah FORGE project by Fervo Energy, presented by Sireesh Dadi. The project's objective was to develop a multistage hydraulic stimulation approach designed specifically to t...
Authors
Dadi, S. and Norbeck, J. Fervo Energy
geothermalenergyannual workshop2023utah forgeegsinjectivitycross-well flowflow ratesflow distributionheat mining efficiencysustained heat transferplug-and-perfstimulationstress heterogeneitystress shadowingthermal breakdownpresentation

Utah FORGE 3-2535: Report on Borehole EM Data Collection and Imaging with the VEMP Field System

Sep 05, 2024
7.81 MB
Publicly accessible
This report outlines electromagnetic field measurements that were made after stimulation at Utah FORGE in May of 2024. The measurements involved lowering an electrode to ~3500' in well 16A to energize the steel casing as part of the electric source, with the return electrode locat...
Authors
Alumbaugh, D. et al Lawrence Berkeley National Laboratory
geothermalenergyelectromagneticresistivityutah forgeegs16aemvempgeophysicsborehole loggingcross-boreholemagnetic inductionthree componentstimulationreportdata collectiondata processing

Utah FORGE: Well 16B(78)-32 Post Hydraulic Fracturing 9 Hour Dual Well Circulation Test Fiber Optic Monitoring Report April 2024

Apr 27, 2024
5.78 MB
Publicly accessible
This report examines the fiber optic measurements made on the Utah FORGE well 16B(78)-32 after it and well 16A(78)-32 were hydraulically stimulated and shortly thereafter a 9 hour cross well circulation test was run between them. The report reviews distributed fiber optic signal p...
Authors
Guzik, A. and Davidson, E. Neubrex Energy Services (US), LLC
geothermalenergyfiber opticsneubrexstraintemperatureflow testcirculationhydraulic fracturingutah forgeegsrayleigh frequency shiftrfsdistributed strain sensingdsspumpingdischargeprocessed datareport16b78-3216a78-32distributed fiber opticsfiber optic monitoring

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

Utah FORGE: Stimulation Crosswell Strain Response Fiber Optic Monitoring Report April 2024

Apr 03, 2024
6.43 MB
Publicly accessible
This report documents the use of fiber optic Rayleigh frequency shift (RFS) Distributed Strain Sensing (DSS), Distributed Temperature Sensing (DTS), and microseismic data recorded during the hydraulic fracture stimulation of well 16A(78)-32, as detected in the offset well 16B(78)-...
Authors
Jurick, D. et al Neubrex Energy Services (US), LLC
geothermalenergystrainmicro seismicdtsdssrfs dsshydraulic fracturingfault reactivationfracture driven interactionfdifrac hitsdistributed temperature sensingdistributed strain sensingprocessed datareportutah forgeneubrexcrosswellfiber optic monitoringgeophysicsstimulation

Utah FORGE: Optimization of a Plug-and-Perf Stimulation (Fervo Energy)

Feb 08, 2023
6.91 MB
Publicly accessible
Information around the plug-and-perf treatment design at Utah FORGE by Fervo Energy. Objective and Purpose: Develop a multistage hydraulic stimulation approach designed specifically to target the top three factors that control the technical and commercial viability of an EGS sys...
Authors
Norbeck, J. et al Fervo Energy
geothermalenergyutah forgeplug-and-perf stimulationwell stimulationfervo energyplug-and-perfplug and perffervotechnicalassessmentfeasibilityhydraulicstimulationinjection testprocessed datablue mountainnevadaegswell 73-22well 34a-22well 34-22near-field egshorizontal drillingproppantheat in placestate of stressfiber optic sensing

A Thermal-Hydrological-Chemical Model for the EGS Demonstration Project at Newberry Volcano, OR

Jan 30, 2012
Size unavailable
Publicly accessible
Newberry Volcano in Central Oregon is the site of a Department of Energy funded Enhanced Geothermal System (EGS) Demonstration Project. Stimulation and production of an EGS is a strong perturbation to the physical and chemical environment, giving rise to coupled Thermal-Hydrologic...
Authors
Sonnenthal, E. et al National Energy Technology Laboratory
geothermalnewberryoregonegsenhanced geothermal systemnewgenthermalhydrologychemicalmodelcross-sectionsstimulationinjectionhydrologicaldemonstrationmechanical

Utah FORGE: Neubrex Well 16B(78)-32 DAS Data April 2024

Oct 01, 2024
97.48 TB
Publicly accessible
This dataset comprises Distributed Acoustic Sensing (DAS) data collected from the Utah FORGE monitoring well 16B(78)-32 (the producer well) during hydraulic fracture stimulation operations conducted in April 2024. The data were acquired continuously over the stimulation period at ...
Authors
Jurick, D. et al Neubrex Energy Services (US), LLC
geothermalenergydasacoustic sensingmicroseismiccrosswell strain ratefracture driven interactionsfdidistributed acoustic sensinginjection allocationstrain rateutah forgeegsstimulation16b 78-3216a 78-32mircroseismicityneubrexraw datahdf5h5time gated

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

EGS Collab: Modeling and Simulation Working Group Teleconference Series (1-98)

Feb 04, 2020
11.93 GB
Publicly accessible
This submission contains the presentation slides and recordings from the first 98 EGS Collab Modeling and Simulation Working Group teleconferences. These teleconferences served three objectives for the project: 1) share simulation results, 2) communicate field activities and resul...
Authors
White, M. et al Pacific Northwest National Laboratory
geothermalenergyegs collabsurfhydraulicfracturingstimulationsanford underground research facilityexperimentegsmodelingtemperatureheat flowdtstracerpressureinjection testflowc-dots
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