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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

Soda Lake Geothermal: Raw 3D and 3C Seismic-Reflection Data from 2010 Survey

Sep 01, 2010
172.11 GB
Publicly accessible
This dataset contains seismic-reflection records created in 2010 around the Soda Lake geothermal field near Fallon, Nevada. The data was collected by the power plant operator at the time, Magma Energy (CYRQ Energy in 2024). This was a petroleum-industry-quality three-dimensional ...
Authors
N. Louie, J. et al University of Nevada Reno
geothermalenergysoda lake geothermalseismic dataraw data3dseismic reflectionseg-yfield logsproject reportssoda lakenevadavibroseisfallon3cshot recordsfield recordssurveyseismic surveymagmageophysics

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

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

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

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

Cape EGS: Seismic Attenuation Profile and DAS Microseismic P-wave Spectra

Mar 17, 2026
15.25 GB
Publicly accessible
This dataset contains a 1D P-wave attenuation (Q) profile, distributed acoustic sensing (DAS) microseismic P-wave spectra, and derived source parameters from the Delano 1OB well at the Cape Modern geothermal field. The data were collected during a stimulation period from mid-Febru...
Authors
Chang, H. et al Lamont Doherty Earth Observatory
geothermalenergydasfiber-opticattenuationmicroseismicityp-wavesource parametersstress dropcapeforgeqspectraseismicegscape modernutah forgedistributed acoustic sensingp-wave attenuationquality factorbrune modelcorner frequencyseismic momentmoment magnitudewell logsdownhole measurementsraw dataprocessed datageomechanicsgeophysics

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

GOOML Big Kahuna Forecast Modeling and Genetic Optimization Files

Jun 30, 2021
13.6 MB
Publicly accessible
This submission includes example files associated with the Geothermal Operational Optimization using Machine Learning (GOOML) Big Kahuna fictional power plant, which uses synthetic data to model a fictional power plant. A forecast was produced using the GOOML data model framework ...
Authors
Buster, G. et al Upflow
geothermalenergymachine learningoptimizationoperationssynthetic datapower plantbig kahunagoomlgenetic optimizationforecastinputsoutputsconfigurationexamplephygnnphysics guided neural networkssteamfieldsteam fieldwellsflash plantsneural networkdataprocessed datacodepythonsimulationmodel

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

Utah FORGE: Fault Reactivation Through Fluid Injection Induced Seismicity Laboratory Experiments

Jul 01, 2023
119.91 MB
Publicly accessible
Included are results from shear reactivation experiments on laboratory faults pre-loaded close to failure and reactivated by the injection of fluid into the fault. The sample comprises a single-inclined-fracture (SIF) transecting a cylindrical sample of Westerly granite. All expe...
Authors
Yu, J. et al Pennsylvania State University
energyinduced seismicityegsutah forgewesterly graniteraw datacodematlabfault activationinjection testpressureflow ratereactivationshearfluid

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
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