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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

Utah FORGE: Seismic Velocity Models, February 2021

This dataset contains a map, showing the Utah FORGE seismic stations, and seismic velocity model data. There are 61 1-D velocity models which are in a compressed TAR file. A paper is referenced at the end of this description which discusses the use of these data in 3D modelling. T...
Pankow, K. Energy and Geoscience Institute at the University of Utah
Feb 28, 2021
3 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: 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

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

High-Temperature Self-Healing Geothermal Cement Composites

A presentation with notes showing an overview of the last 6 months of the project on high-temperature self-healing inorganic cement composites. General approach, test methods and results for the self-healing cement composites are presented. Data include strength recoveries for 9 c...
Pyatina, T. and Sugama, T. Brookhaven National Laboratory
Mar 21, 2017
1 Resources
0 Stars
Publicly accessible

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

This data set 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. . et al National Renewable Energy Laboratory
Dec 23, 2024
2 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. . et al National Renewable Energy Laboratory
Oct 21, 2024
1 Resources
0 Stars
Publicly accessible

Walker Ranch 3D Seismic Images

Amplitude images (both vertical and depth slices) extracted from 3D seismic reflection survey over area of Walker Ranch area (adjacent to Raft River). Crossline spacing of 660 feet and inline of 165 feet using a Vibroseis source. Processing included depth migration. Micro-earthqua...
J., R. Lawrence Livermore National Laboratory
Mar 01, 2016
2 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

Hawaii Play Fairway Analysis: Recharge Data for Hawaii Island

Recharge data for Hawaii Island in shapefile format. The data are from the following sources: Whittier, R.B and A.I. El-Kadi. 2014. Human Health and Environmental Risk Ranking of On-Site Sewage Disposal systems for the Hawaiian Islands of Kauai, Molokai, Maui, and Hawaii Final, ...
Lautze, N. University of Hawaii
Jan 01, 2015
8 Resources
0 Stars
Publicly accessible

Microbial Taxa Distribution Data From 16S rRNA Analysis Of Desalination Operations At Carlsbad, CA And Tampa Bay, FL

This data set list the distribution of microbial taxa from three sets of sampling campaigns from unit operations in two large desalination facilities in the US conducted between March and May 2021. The desalination plants include the Claude "Bud" Lewis Carlsbad Desalination Plant ...
Kumar, M. et al University of Texas
Sep 24, 2021
3 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

DEEPEN 3D PFA Weights for Exploration Datasets in Magmatic Environments

DEEPEN stands for DE-risking Exploration of geothermal Plays in magmatic ENvironments. As part of the development of the DEEPEN 3D play fairway analysis (PFA) methodology for magmatic plays (conventional hydrothermal, superhot EGS, and supercritical), weights needed to be develop...
Taverna, N. et al National Renewable Energy Laboratory
Jun 30, 2023
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
In curation

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

Utah FORGE 2-2439: A Multi-Component Approach to Characterizing In-Situ Stress: Laboratory, Modeling and Field Measurement Workshop Presentation

This is a presentation on A Multi-Component Approach to Characterizing In-Situ Stress at the U.S DOE FORGE EGS Site: Laboratory, Modeling and Field Measurement project by Battelle [Columbus, OH], presented by Mark Kelley. The project's objective was to characterize stress in the U...
Kelley, M. and Bunger, A. Battelle Memorial Institute
Sep 08, 2023
1 Resources
0 Stars
Publicly accessible

Summary of Cement Formulations Tested by BNL for Self-Healing Ability Tests Conditions and Data

A table of cement formulations tested by Brookhaven National Laboratory in 2016-2017 in the frame of the "Self-healing and Re-Adhering Cements with Improved Toughness at Casing and Formation Interfaces for Geothermal Wells" project.
Sugama, T. Brookhaven National Laboratory
Sep 27, 2017
2 Resources
0 Stars
Publicly accessible

Processed Lab Data for Neural Network-Based Shear Stress Level Prediction

Machine learning can be used to predict fault properties such as shear stress, friction, and time to failure using continuous records of fault zone acoustic emissions. The files are extracted features and labels from lab data (experiment p4679). The features are extracted with a n...
Marone, C. et al Pennsylvania State University
May 14, 2021
3 Resources
0 Stars
Publicly accessible

G2Aero Database of Airfoils Curated Airfoils

This dataset contains a curated set of 19,164 airfoil shapes from various applications and the data-driven design space of separable shape tensors (PGA space), which can be used as a parameter space for machine-learning applications focused on airfoil shapes. We constructed the a...
Doronina, O. et al National Renewable Energy Lab NREL
Sep 24, 2024
3 Resources
0 Stars
Publicly accessible

DEEPEN Global Standardized Categorical Exploration Datasets for Magmatic Plays

DEEPEN stands for DE-risking Exploration of geothermal Plays in magmatic ENvironments. As part of the development of the DEEPEN 3D play fairway analysis (PFA) methodology for magmatic plays (conventional hydrothermal, superhot EGS, and supercritical), weights needed to be develop...
Taverna, N. et al National Renewable Energy Laboratory
Jun 30, 2023
4 Resources
0 Stars
Publicly accessible

Desert Peak Geodatabase for Geothermal Exploration Artificial Intelligence

These files contain the geodatabases related to the Desert Peak Geothermal Field. It includes all input and output files used in the project. The files include data categories of raw data, pre-processed data, and analysis (post-processed data). In each of these categories there ar...
Moraga, J. et al Colorado School of Mines
Apr 27, 2021
3 Resources
0 Stars
Publicly accessible

Brady Geodatabase for Geothermal Exploration Artificial Intelligence

These files contain the geodatabases related to Brady's Geothermal Field. It includes all input and output files for the Geothermal Exploration Artificial Intelligence. Input and output files are sorted into three categories: raw data, pre-processed data, and analysis (post-proces...
Moraga, J. et al Colorado School of Mines
Apr 27, 2021
3 Resources
0 Stars
Publicly accessible
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