19 datasets found
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Federal
BUTTER-E - Energy Consumption Data for the BUTTER Empirical Deep Learning Dataset
Department of Energy —
The BUTTER-E - Energy Consumption Data for the BUTTER Empirical Deep Learning Dataset adds node-level energy consumption data from watt-meters to the primary sweep of... -
Federal
Brady Geodatabase for Geothermal Exploration Artificial Intelligence
Department of Energy —
These files contain the geodatabases related to Brady's Geothermal Field. It includes all input and output files for the Geothermal Exploration Artificial... -
Federal
BuildingsBench: A Large-Scale Dataset of 900K Buildings and Benchmark for Short-Term Load Forecasting
Department of Energy —
The BuildingsBench datasets consist of: - Buildings-900K: A large-scale dataset of 900K buildings for pretraining models on the task of short-term load forecasting... -
Federal
Programs and Code for Geothermal Exploration Artificial Intelligence
Department of Energy —
The scripts below are used to run the Geothermal Exploration Artificial Intelligence developed within the "Detection of Potential Geothermal Exploration Sites from... -
Federal
BUTTER - Empirical Deep Learning Dataset
Department of Energy —
The BUTTER Empirical Deep Learning Dataset represents an empirical study of the deep learning phenomena on dense fully connected networks, scanning across thirteen... -
Federal
Data Arrays for Microearthquake (MEQ) Monitoring using Deep Learning for the Newberry EGS Sites
Department of Energy —
The 'Machine Learning Approaches to Predicting Induced Seismicity and Imaging Geothermal Reservoir Properties' project looks to apply machine learning (ML) methods to... -
Federal
Sentinel-1 Input Data for PSInSAR Analysis
Department of Energy —
Files used to perform the Persistent Scatterer InSAR analysis with SARPROZ. The data is sourced from ESAs Sentinel-1 project and covers Brady Hot Springs and Desert... -
Federal
Active Source Seismic (Ultrasonic) Data from Double-Direct Shear Lab Experiments
Department of Energy —
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... -
Federal
EGS Collab Experiment 1: 3D Seismic Velocity Model and Updated Microseismic Catalog Using Transfer-Learning Aided Double-Difference Tomography
Department of Energy —
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... -
Federal
Salton Sea Geodatabase for Geothermal Exploration Artificial Intelligence
Department of Energy —
These files contain the geodatabases related to Salton Sea Geothermal Field. It includes all input and output files used with the Geothermal Exploration Artificial... -
Federal
Desert Peak Geodatabase for Geothermal Exploration Artificial Intelligence
Department of Energy —
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... -
Federal
Utah FORGE: Focal Mechanism Catalog from Stage 3 of the April 2022 Stimulation Test
Department of Energy —
This submission includes focal-mechanism solutions derived from the Utah FORGE April 2022 Stage-3 stimulation. Waveforms were extracted around each event (short... -
Federal
Processed Lab Data for Neural Network-Based Shear Stress Level Prediction
Department of Energy —
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... -
Federal
Utah FORGE 2-2439v2: Reports on Stress Prediction and Modeling for Well 16B(78)-32 - May 2025
Department of Energy —
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... -
Federal
Utah FORGE 3-2535: Preliminary Report on Development of a Reservoir Seismic Velocity Model
Department of Energy —
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... -
Federal
Utah FORGE 6-3712: Probabilistic Estimation of Seismic Response Using Physics-Informed Recurrent Neural Networks - 2024 Annual Workshop Presentation
Department of Energy —
This is a presentation on the Probabilistic Estimation of Seismic Response Using Physics-Informed Recurrent Neural Networks by GTC Analytics, presented by Jesse... -
Federal
Appendices for Geothermal Exploration Artificial Intelligence Report
Department of Energy —
The Geothermal Exploration Artificial Intelligence looks to use machine learning to spot geothermal identifiers from land maps. This is done to remotely detect... -
Federal
Utah FORGE 6-3712: Report on Building a Recurrent Neural Network Framework for Induced Seismicity - October, 2025
Department of Energy —
This is a technical report for the Probabilistic Estimation of Seismic Response Using Physics Informed Recurrent Neural Networks project. The report describes the...
19 datasets found