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Data for Uncontained Ruptures Reduce Energetics of Triggered Seismicity: Laboratory Fault Reactivation Experiments

Apr 13, 2026
43.25 MB
Publicly accessible
The dataset contains raw mechanical data from laboratory fault reactivation experiments on pre-stressed granite/granitoid samples, along with experimental parameters and MATLAB processing code for data deduction. The raw time-series data were recorded using a triaxial-shear appara...
Authors
Elsworth, D. et al Pennsylvania State University
injection-induced seismicityfault pre-stressseismic moment scalingrupture regimesinduced seismicitytriggered seismicityfault reactivationfluid injectionearthquake magnitudeforecastingrupture mechanicscontained ruptureuncontained ruptureseismic momentlaboratory experimentsraw datatriaxial sheargranitegranitoidgeomechanicsshear displacementaxial displacementmatlab

Pilgrim Hot Springs: GEOPHIRES Inputs and Outputs for Direct-Use Geothermal District Heating and Cooling

Mar 21, 2024
211.86 kB
Publicly accessible
This dataset includes files for a techno-economic analysis conducted using the GEOPHIRES simulator to examine the feasibility of expanding a larger district heating site in a remote location: Pilgrim Hot Springs, Alaska. Files included here are GEOPHIRES inputs and outputs for fiv...
Authors
Pauling, H. et al National Renewable Energy Laboratory
geothermalenergygeophireschporcparallel cycletopping cyclepilgrim hot springsalaskatechno-economic analysisfeasibilityteareservoir simulationsheat demandcapitaloperating costsdistrict geothermaldistrict heatingmodelmodelingpythongithubinputsoutputs

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

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

Deep Direct-Use Feasibility Study Economic Analysis using GEOPHIRES for West Virginia University

Jan 09, 2020
3.73 MB
Publicly accessible
This dataset contains all the inputs used and output produced from the modified GEOPHIRES for the economic analysis of base case hybrid GDHC system, improved hybrid GDHC system with heat pump and for hot water GDHC. Software required: Microsoft Notepad, Microsoft Excel and GEOPHI...
Authors
Garapati, N. West Virginia University
geothermalenergygeophireswvulcohhybrid geothermal natural ags systemdirect-usereservoir simulationuncertainty analysisddudeep direct usefeasibilityeconomicgdhcdhsdistrict heatingdistrict heating and coolingcostheatlevelizedhot waterhybridheat pumpnatural gashybrid geothermal natural gas system

Matlab Scripts and Sample Data Associated with Water Resources Research Article

Jul 18, 2015
487.87 MB
Publicly accessible
Scripts and data acquired at the Mirror Lake Research Site, cited by the article submitted to Water Resources Research: Distributed Acoustic Sensing (DAS) as a Distributed Hydraulic Sensor in Fractured Bedrock M. W. Becker(1), T. I. Coleman(2), and C. C. Ciervo(1) 1 California St...
Authors
Becker, M. and Coleman, T. California State University
geothermalenergydistributed acoustic sensingfractured rockmatlabboreholefse9silixa idasdasdistributed hydraulic sensinggeologyfracturedbedrockmirror lakewell dataraw datadisplacementfftdecimatedstep test

Utah FORGE 2-2446: Connecting In Situ Stress and Wellbore Deviation to Near-Well Fracture Complexity using Phase-Field Simulations

Jan 30, 2025
10.44 MB
Publicly accessible
This report presents a series of numerical experiments investigating the relationships among near-well fracture complexity, in situ stress conditions, and wellbore deviation. Using a phase-field modeling approach, the study explores how factors such as stress regimes, wellbore ori...
Authors
Cusini, M. and Fei, F. Lawrence Livermore National Laboratory
geothermalenergyutah forgephase fieldnumerical simulationnear wellbore fracture nucleationegsnear-wellfracture complexityin situ stresswellbore deviationphase-field modelingnumerical solutionsfracture nucleationgeos modelingstress regimesfracture propagationrock mechanicstechnical report

Community Geothermal: Seward Alaska Heat Loop District Energy System Modelica Model

Sep 29, 2024
Size unavailable
In progress
This dataset contains a Modelica-based dynamic thermal simulation model of the Seward Heat Loop project. The model contains building loads generated from DesignBuilder simulations of the four city-owned buildings that are connected to the system. These buildings are heated by a hy...
Authors
Mitchell, M. et al National Renewable Energy Laboratory
geothermalenergyheat pumpocean sourcewell datacommgeo

EGS Collab Experiment 1: Microseismic Monitoring

Jul 29, 2019
2.83 TB
Publicly accessible
The U.S. Department of Energy's Enhanced Geothermal System (EGS) Collab project aims to improve our understanding of hydraulic stimulations in crystalline rock for enhanced geothermal energy production through execution of intensely monitored meso-scale experiments. The first expe...
Authors
Schoenball, M. et al Lawrence Berkeley National Laboratory
geothermalenergyegs collabsurfhydraulicfracturingstimulationsanford underground research facilityexperimentegsmicroseismic monitoringmeso-scale stimulationssandford underground researchmesoscale experimentscrystalline rock3d sensorleadsouth dakotasta/lta triggering algorithmmicroseismicitycatalograw dataprocessed databinary file interpreterpythongeospatial data

Utah FORGE 2-2446: Characterizing Stress Roughness Through Simulation of Hydraulic Fracture Growth

Jan 30, 2025
2.55 MB
Publicly accessible
This dataset covers work that investigated the apparent toughness anisotropy at Utah FORGE by comparing microseismic data with stress profiles from field measurements. The study analyzes the hydraulic fracture growth of Stage 3 at Well 16A(78)-32 using MEQ data, calibrating a nume...
Authors
Cusini, M. and Fei, F. Lawrence Livermore National Laboratory
geothermalenergyutah forgestress roughnesshydraulic fracturingmeqegsstress profilefield measurementshydraulic fracture growth16a78-32stage 3geostechnical reportprocessed datageophysics2-2446toughness anisotropyrock mechanics

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

Distributed Acoustic Sensing (DAS) Data for Periodic Hydraulic Tests: Hydraulic Data

Jul 31, 2015
4.26 MB
Publicly accessible
Hydraulic responses from periodic hydraulic tests conducted at the Mirror Lake Fractured Rock Research Site, during the summer of 2015. These hydraulic responses were measured also using distributed acoustic sensing (DAS) which is cataloged in a different submission under this gr...
Authors
Cole, M. California State University
geothermalenergyperiodic hydraulic testsinterference testsdaspulse interference testsdistributed acoustic sensinghydraulic testingmatlabacoustic sensing data

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

PoroTomo Natural Laboratory Horizontal and Vertical Distributed Acoustic Sensing Data

Mar 29, 2016
342.13 TB
Publicly accessible
This dataset includes links to the PoroTomo DAS data in both SEG-Y and hdf5 (via h5py and HSDS with h5pyd) formats with tutorial notebooks for use. Data are hosted on Amazon Web Services (AWS) Simple Storage Service (S3) through the Open Energy Data Initiative (OEDI). Also include...
Authors
Feigl, K. et al University of Wisconsin
geothermalporotomodasfiber opticsurface sensorsseismic arraydistributed acoustic sensingporoeleastic tomographybradys geothermal fieldgeosciencedistributed sensingdownholetrenchedseismicityhydrothermalgeophysicsoediraw datajupyter notebookpythonhdf5hsdsh5pyh5pyd

Machine Learning-Assisted High-Temperature Reservoir Thermal Energy Storage Optimization: Numerical Modeling and Machine Learning Input and Output Files

Apr 15, 2022
113.79 MB
Publicly accessible
This data set includes the numerical modeling input files and output files used to synthesize data, and the reduced-order machine learning models trained from the synthesized data for reservoir thermal energy storage site identification. In this study, a machine-learning-assiste...
Authors
Jin, W. et al Idaho National Laboratory
reservoir thermal energy storagestochastic simulationgeotesmachine learningmodelingtesht-rtescharacterizationnumerical modelstochastichydrogeologic formationsimulated datasimulation datahigh-temperaturethermal energy storageoptimizationartificial neural network regressionannneural networkoperation scenariosseasonal-cyclepareto frontsseasonal operationcontinuous operationfalconmoose

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
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