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Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs

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...
Beckers, K. et al National Renewable Energy Laboratory
Feb 18, 2021
1 Resources
0 Stars
Publicly accessible

GeoThermalCloud: Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration and Development of Hidden Geothermal Resources

Geothermal exploration and production are challenging, expensive and risky. The GeoThermalCloud uses Machine Learning to predict the location of hidden geothermal resources. This submission includes a training dataset for the GeoThermalCloud neural network. Machine Learning for Di...
Ahmmed, B. Stanford University
Apr 04, 2022
3 Resources
0 Stars
Publicly accessible

Utah FORGE 2-2439v2: Report on Predicting Far-Field Stresses Using Finite Element Modeling and Near-Wellbore Machine Learning for Well 16A(78)-32

This report presents the far-field stress predictions at two locations along the vertical section of Utah FORGE Well 16A (78)-32 using a physics-based thermo-poro-mechanical model. Three principal stresses in far-field were obtained by solving an inverse problem based on the near-...
Lu, G. et al University of Pittsburgh
Aug 30, 2024
2 Resources
0 Stars
Publicly accessible

EGS Collab Experiment 1: 3D Seismic Velocity Model and Updated Microseismic Catalog Using Transfer-Learning Aided Double-Difference Tomography

This package contains a 3D Seismic velocity model and an updated microseismic catalog associated with a proceedings paper (Chai et al., 2020) published in the 45th Workshop on Geothermal Reservoir Engineering. The 3D_seismic_velocity_model text file contains x (m), y(m), z(m), P-w...
Chai, C. et al Oak Ridge National Laboratory
Apr 20, 2020
7 Resources
0 Stars
Publicly accessible

GOOML Big Kahuna Forecast Modeling and Genetic Optimization Files

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 ...
Buster, G. et al Upflow
Jun 30, 2021
11 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

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

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

Control-based optimization for tethered tidal kite

This submission includes three peer-reviewed (under review) papers from the researchers at North Carolina State University presenting control-based techniques to maximize effectiveness of a tethered tidal kite. Below are the abstracts of each file included in the submission. Cobb...
Vermillion, C. et al North Carolina State University
Mar 02, 2020
3 Resources
0 Stars
Publicly accessible

Coso Geothermal Spectral Library for Rocks and Minerals

An integrated open mineral spectral library designed to enhance the utility and precision of mineral spectral data for geothermal exploration, developed from a reliable and comprehensive digital dataset for seamless sharing by integrating field data, the USGS spectral library, and...
Cavur, M. et al Mining Engineering Department of Colorado School of Mines
Aug 23, 2023
5 Resources
0 Stars
Publicly accessible

Surface Complexation Modeling of Terbium Biosorption onto E. Coli Bacterial Surfaces with Lanthanide Binding Tags

Lanthanide binding tags (LBTs) have been engineered onto native Escherichia coli (E. coli) bacterial surfaces to enhance extraction and recovery of rare earth elements (REEs). Three strains of E. coli were studied: (1) the native E. coli surface, (2) a mutant E. coli surface with ...
Jiao, Y. Lawrence Livermore National Laboratory
Apr 01, 2018
1 Resources
0 Stars
Publicly accessible

Evaluation of Crawlspace Retrofits in Multifamily Buildings

In 2011 and early 2012, Building Science Corporation (BSC) collaborated with Innova Services Corporation on a multifamily community un-vented crawlspace retrofit project at Oakwood Gardens in Lansdale, Pennsylvania. BSC provided design consulting services and pre and post-retrofit...
Rudd, A. Advanced Building Systems
Apr 27, 2016
41 Resources
0 Stars
Publicly accessible

TEAMER: Experimental Validation and Analysis of Deep Reinforcement Learning Control for Wave Energy Converters

Through this TEAMER project, Michigan Technological University (MTU) collaborated with Oregon State University (OSU) to test the performance of a Deep Reinforcement Learning (DRL) control in the wave tank. Unlike model-based controls, DRL control is model-free and can directly max...
Zou, S. et al Michigan Technological University
Mar 07, 2025
7 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 3-2535: Preliminary Report on Development of a Reservoir Seismic Velocity Model

This report describes the development of a preliminary 3D seismic velocity model at the Utah FORGE site and first results from estimating seismic resolution in the generated fracture volume during Stage 3 of the April 2022 stimulation. A preliminary 3D velocity model for the larg...
Gritto, R. Array Information Technology
Jan 30, 2023
1 Resources
0 Stars
Publicly accessible

Appendices for Geothermal Exploration Artificial Intelligence Report

The Geothermal Exploration Artificial Intelligence looks to use machine learning to spot geothermal identifiers from land maps. This is done to remotely detect geothermal sites for the purpose of energy uses. Such uses include enhanced geothermal system (EGS) applications, especia...
Duzgun, H. et al Colorado School of Mines
Jan 08, 2021
12 Resources
0 Stars
Publicly accessible

Recovery of Rare Earth Elements from Geothermal Fluids through Bacterial Cell Surface Adsorption

We summarized the FY17 and part of FY18 results of the analysis of the effect of several parameters (e.g., total dissolved solids, specific competing metals, pH, and temperature) on REE recovery from geothermal brine in a manuscript that was submitted to Environmental Science & Te...
Jiao, Y. et al Lawrence Livermore National Laboratory
Jan 01, 2018
2 Resources
0 Stars
Publicly accessible

Characterizing favourable structural settings of geothermal reservoirs in extensional regions: Enhanced exploration strategies

Exploration of geothermal systems is commonly hampered by the risk of unsuccessful drilling. A major problem in selecting well sites is that the favorable settings of known systems are generally not adequately characterized. This is particularly important in amagmatic regions, wh...
Faulds, J. et al University of Nevada
Nov 30, 2010
1 Resources
0 Stars
Publicly accessible

Field Testing of Compartmentalization Methods for Multifamily Construction Washington DC

BSC TO5 Task 2.1 Field Testing of Compartmentalization Methods for Multifamily Construction Capitol Heights, MD 20743 A building comprising five vertical townhome units was built in the Washington, D.C., area; the townhomes were three-story slab-on-grade units (1700-2000 ft2) wit...
Ueno, K. and Lstiburek, J. Building Science Corporation
Apr 27, 2016
22 Resources
0 Stars
Publicly accessible

OPFLearnData: Dataset for Learning AC Optimal Power Flow

The datasets are resulting from OPFLearn.jl, a Julia package for creating AC OPF datasets. The package was developed to provide researchers with a standardized way to efficiently create AC OPF datasets that are representative of more of the AC OPF feasible load space compared to t...
Joswig-Jones. . et al National Renewable Energy Laboratory
Oct 26, 2021
12 Resources
0 Stars
Publicly accessible

DCIF Westerly Granite AE Stress Effect Test (Task 3-1)

Directional Cooling-Induced Fracturing (DCIF) experiments were conducted on rectangular Westerly granite blocks (width=depth=4.0", height=2.0"). Liquid nitrogen was poured in a small, 1"-diameter copper cup attached to the top of the sample, and the resulting acoustic emissions (A...
Nakagawa, S. and Trzeciak, M. Lawrence Berkeley National Laboratory
Jul 08, 2021
15 Resources
0 Stars
Publicly accessible

INTEGRATE Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements

The INTEGRATE (Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements) project is developing a new inverse-design capability for the aerodynamic design of wind turbine rotors using invertible neural networks. This AI-based design techno...
Vijayakumar, G. et al National Renewable Energy Laboratory (NREL)
May 04, 2021
8 Resources
0 Stars
Publicly accessible

Paisley Oregon Geothermal Plant Operated by Surprise Valley Electrification 2016 Operational Information

This submission includes an Electricity Generation Summary, Maintenance Logs, Detailed Operations Data, Operating Cost Summary, and an Operations overview at the Paisley Oregon Geothermal Plant. Data uploaded for SVEC by Tom Williams, NREL
Culp, E. Surprise Valley Electrification Corp. (SVEC)
Jan 01, 2017
5 Resources
0 Stars
Publicly accessible

Developing Successful Exploration Strategies in Extended Terranes

We conducted a comprehensive analysis of the structural controls of geothermal systems within the Great Basin and adjacent regions. Our main objectives were to: 1) Produce a catalogue of favorable structural environments and models for geothermal systems. 2) Improve site-specifi...
E., J. University of Nevada
Dec 31, 2013
1 Resources
0 Stars
Publicly accessible

WHOLESCALE: Microseismic Event Catalog for San Emidio, Nevada 2022

This submission includes a high-precision seismic event catalog estimated from seismic data collected at San Emidio, Nevada from April to May 2022. The catalog lists the precise time, location, and magnitude of microseismic events recorded during this period. Both the seismic dat...
Guo, H. et al University of Wisconsin Madison
Apr 20, 2024
3 Resources
0 Stars
Publicly accessible
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