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"Support Vector Machine"×

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

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...
Jin, W. et al Idaho National Laboratory
Apr 15, 2022
4 Resources
0 Stars
Publicly accessible

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

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...
Siler, D. et al United States Geological Survey
Oct 01, 2021
6 Resources
0 Stars
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Active Source Seismic (Ultrasonic) Data from Double-Direct Shear Lab Experiments

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...
Marone, C. Pennsylvania State University
May 05, 2021
1 Resources
0 Stars
Publicly accessible

Topology-Based Machine-Learning for Modeling Power-System Responses to Contingencies

This is the companion dataset to the presentation NREL/PR-6A20-77485, which was presented at the 2020 Joint Statistical Meeting on August 3, 2020. Developed for the machine-learning predictive modeling of power-system responses to disruptions, it contains results of power-system c...
Bush, B. National Renewable Energy Laboratory
Aug 01, 2020
2 Resources
0 Stars
Publicly accessible

Utah FORGE 2439: Machine Learning for Well 16A(78)-32 Stress Predictions September 2023 Report

This task completion report documents the development and implementation of machine learning (ML) models for the prediction of in-situ vertical (Sv), minimum horizontal (SHmin) and maximum horizontal (SHmax) stresses in well 16A(78)-32. The detailed description of the experimental...
Mustafa, A. et al Battelle Memorial Institute
Sep 28, 2023
3 Resources
0 Stars
Publicly accessible

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

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...
Elsworth, D. and Marone, C. Pennsylvania State University
Nov 22, 2022
4 Resources
0 Stars
Publicly accessible

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

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...
Zhu, T. Pennsylvania State University
May 05, 2021
4 Resources
0 Stars
Publicly accessible

Utah FORGE 2-2439v2: Reports on Stress Prediction and Modeling for Well 16B(78)-32 May 2025

These two reports from the University of Pittsburgh document related efforts under Utah FORGE Project 2-2439v2 to estimate in-situ stresses in well 16B(78)-32 using laboratory data, machine learning models, and physics-based simulations. One report focuses on developing and valida...
Lu, G. et al University of Pittsburgh
Jun 05, 2025
2 Resources
0 Stars
Publicly accessible

EGS Collab Experiment 1: In-situ observation of pre-, co and post-seismic shear slip preceding hydraulic fracturing

Understanding the initiation and arrest of earthquakes is one of the long-standing challenges of seismology. Here we report on direct observations of borehole displacement by a meter-sized shear rupture induced by pressurization of metamorphic rock at 1.5 km depth. We observed the...
Guglielmi, Y. et al Lawrence Berkeley National Laboratory
May 22, 2018
2 Resources
0 Stars
Publicly accessible

Utah FORGE 2-2439v2: Characterizing In-Situ Stress with Laboratory Modelling and Field Measurements 2024 Annual Workshop Presentation

This is a presentation on A Multi-Component Approach to Characterizing In-Situ Stress at the Utah FORGE Site: Laboratory Modelling and Field Measurements project by The University of Pittsburgh, presented by Andrew Bunger. The project characterizes the stress in the Utah FORGE EGS...
Bunger, A. Energy and Geoscience Institute at the University of Utah
Sep 04, 2024
1 Resources
0 Stars
Publicly accessible

National Residential Efficiency Measures Database (REMDB)

This project provides a national unified database of residential building retrofit measures and associated retail prices and end-user might experience. These data are accessible to software programs that evaluate most cost-effective retrofit measures to improve the energy efficien...
Moore, N. et al National Renewable Energy Lab NREL
Sep 29, 2023
5 Resources
0 Stars
Publicly accessible

Utah FORGE 6-3629: Application of Machine Learning, Geomechanics, and Seismology for Real-Time Decision Making Tools During Stimulation 2025 Workshop Presentation

This is a presentation on the Cutting Edge Application of Machine Learning, Geomechanics, and Seismology for Real-Time Decision Making Tools During Stimulation by the University of Utah, presented by Dr. No'am Zach Dvory. This video slide presentation, by the University of Utah, d...
Dvory, N. University of Utah
Sep 18, 2025
3 Resources
0 Stars
Publicly accessible

Utah FORGE 6-3656: Real-Time Traffic Light System and Reservoir Engineering with Seismicity Forecasting and Ground Motion Prediction 2025 Workshop Presentation

This is a presentation on Real-Time Robust Adaptive Traffic Light System and Reservoir Engineering with Machine-Learning-Based Seismicity Forecasting and Data-Driven Ground Motion Prediction (RT Forecast) by Lawrence Berkeley National Laboratory, presented by Nori Nakata. This vid...
Nakata, N. Lawrence Berkeley National Laboratory
Sep 18, 2025
3 Resources
0 Stars
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Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs Results

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...
Beckers, K. et al National Renewable Energy Laboratory
Oct 20, 2021
6 Resources
0 Stars
Publicly accessible

Utah FORGE: InSAR Data 2019

This dataset contains Interferometric Synthetic Aperture Radar (InSAR) data used for ground deformation monitoring during Phase 2C of the Utah FORGE project. The dataset includes measurements of the mean rate of range change and associated standard errors, provided in both CSV and...
Feigl, K. et al Energy and Geoscience Institute at the University of Utah
Jul 01, 2019
2 Resources
0 Stars
Publicly accessible

Fuel Cell Inverter Transition Between Modes of Operation (Grid-Forming and Grid-Following)

This dataset shows the operation of the fuel cell inverter under grid-forming mode of operation, grid-following mode of operation and transition between the two modes.
Nemsow, N. et al National Renewable Energy Laboratory
Dec 23, 2024
2 Resources
0 Stars
Publicly accessible

Geologic Map and Cross Sections of the McGinness Hills Geothermal Area GIS Data

Geologic map data in shapefile format that includes faults, unit contacts, unit polygons, attitudes of strata and faults, and surficial geothermal features. 5 cross-sections in Adobe Illustrator format. Comprehensive catalogue of drill-hole data in spreadsheet, shapefile, and Ge...
E., J. University of Nevada
Dec 31, 2013
1 Resources
0 Stars
Publicly accessible

Fuel Cell Inverter Dataset

This data set contains the three phase AC voltage, three phase AC current, DC voltage and DC current. These data sets were captured during fuel cell inverter operation in grid-connected dispatch, islanded load changes, transition from grid-connected mode to islanded mode and vice-...
Prabakar, K. et al National Renewable Energy Laboratory
Oct 21, 2024
1 Resources
0 Stars
Publicly accessible

NREL GIS data: Bhutan Wind Power Density at 50m Above Ground Level

GIS data for Bhutan's Wind Power Density at 50m Above Ground Level. NREL developed estimates of Bhutans wind resources at a spatial resolution of 1 km^2 using NREL's Wind Resource Assessment and Mapping System (WRAMS). Wind turbine output at a given site can be predicted using win...
Heimiller, D. et al National Renewable Energy Laboratory
Nov 25, 2014
3 Resources
0 Stars
Publicly accessible

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

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...
Williams, J. Energy and Geoscience Institute at the University of Utah
Sep 17, 2024
1 Resources
0 Stars
Publicly accessible

Super-Resolution for Renewable Energy Resource Data with Climate Change Impacts (Sup3rCC)

The Super-Resolution for Renewable Energy Resource Data with Climate Change Impacts (Sup3rCC) data is a collection of 4km hourly wind, solar, temperature, humidity, and pressure fields for the contiguous United States under various climate change scenarios. Sup3rCC is downscaled ...
Buster, G. et al National Renewable Energy Laboratory (NREL)
Apr 19, 2023
7 Resources
2 Stars
Publicly accessible

BOBr Processed Breaking Wave Data, Agate Beach, OR

This data was recorded by the BOBr (Buoy to Observe Breaking) off the coast of Newport, OR at Agate Beach in the surf zone. The data was recorded by a 9dof inertial measurement unit and consists of a timestamp, quaternion orientation, acceleration vector, rotation vector, and mag...
C, A. Oregon State University
Oct 31, 2013
17 Resources
0 Stars
Publicly accessible

Altona Field Lab Inverse Model WRR 2020

Includes data for measured inert tracer breakthrough curves first reported in Hawkins (2020) (Water Resources Research). In addition, this submission includes the production well temperature measurements first reported in Hawkins et al. (2017a) (Water Resources Research, volume 53...
Tester, J. Cornell University
Jan 01, 2015
3 Resources
0 Stars
Publicly accessible

Artificial Intelligence for Robust Integration of AMI and Synchrophasor Data to Significantly Boost Solar Adoption

The overarching goal of the project is to create a highly efficient framework of machine learning (ML) methods that provide consistent and accurate real-time knowledge of system states from diverse advanced metering infrastructure (AMI) devices and phasor measurement units (PMUs) ...
Ayyanar, R. et al Arizona State University
Feb 01, 2025
12 Resources
0 Stars
Publicly accessible

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

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...
Williams, J. GTC Analytics
Sep 18, 2025
3 Resources
0 Stars
Publicly accessible
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