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USGS Geophysics, Heat Flow, and Slip and Dilation Tendency Data used in Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada
This package contains USGS data contributions to the DOE-funded Nevada Geothermal Machine Learning Project, with the objective of developing a machine learning approach to identifying new geothermal systems in the Great Basin. This package contains three major data products (geoph...
DeAngelo, J. et al Nevada Bureau of Mines and Geology
Jun 01, 2021
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1 Resources
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Dataset for Evaluation of Extreme Weather Impacts on Utility-Scale Photovoltaic Plant Performance in the United States
This dataset is a fusion of three data types (operations and maintenance tickets, weather data, and production data) that was used to support machine learning analysis and evaluation of drivers for low performance at photovoltaic (PV) sites during compound, extreme weather events....
Gunda, T. and Jackson, N. Sandia National Laboratories
Apr 01, 2021
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2 Resources
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Publications and Datasets from Play-Fairway Retrospective Analysis with Emphasis on Developing Improved Hydrothermal Energy Assessments
Previous moderate and high-temperature geothermal resource assessments of the western United States utilized data-driven methods and expert decisions to estimate resource favorability. Although expert decisions can add confidence to the modeling process by ensuring reasonable mode...
Mordensky, S. et al United States Geological Survey
Feb 07, 2023
7 Resources
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7 Resources
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Python Codebase and Jupyter Notebooks Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada
Git archive containing Python modules and resources used to generate machine-learning models used in the "Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada" project. This software is licensed as free to use, modify, a...
Brown, S. and Smith, C. Nevada Bureau of Mines and Geology
Jun 30, 2022
4 Resources
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4 Resources
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Utah FORGE Project 2439: Machine Learning for Well 16A(78)-32 Stress Predictions
This report reviews the training of machine learning algorithms to laboratory triaxial ultrasonic velocity data for Utah FORGE Well 16A(78)-32. Three machine learning (ML) predictive models were developed for the prediction of vertical and two orthogonally oriented horizontal str...
Kelley, M. et al Battelle Memorial Institute
Jun 19, 2023
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1 Resources
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Dynamic Earth Energy Storage: Terawatt-Year, Grid-Scale Energy Storage using Planet Earth as a Thermal Battery (GeoTES): Seedling Project Final Report
Grid-scale energy storage has been identified as a needed technology to support the continued build-out of intermittent renewable energy resources. As of April 2017, the U.S. had approximately 24.2 GW of energy storage on line, compared to 1,081 GW of installed generation capacity...
McLing, T. et al Idaho National Laboratory
May 31, 2019
11 Resources
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11 Resources
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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
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11 Resources
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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
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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
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4 Resources
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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
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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
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6 Resources
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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
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4 Resources
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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
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4 Resources
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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
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6 Resources
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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
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3 Resources
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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
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12 Resources
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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
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3 Resources
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U.S. Wind Siting Regulation and Zoning Ordinances
A machine readable collection of documented wind siting ordinances at the state and local (e.g., county, township) level throughout the United States. The data were compiled from several sources including, DOE's Wind Exchange Ordinance Database (Linked in the submission), National...
Lopez, A. et al National Renewable Energy Laboratory
Jun 30, 2022
4 Resources
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4 Resources
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MOIS CAD Models
SolidWorks models of the Modular Ocean Instrumentation System (MOIS) data acquisition system components in it's subsea enclosure. The zip file contains all the components necessary for the assembly.
Nelson, E. National Renewable Energy Laboratory
Dec 03, 2015
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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
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3 Resources
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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
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3 Resources
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Salton Sea Geodatabase for Geothermal Exploration Artificial Intelligence
These files contain the geodatabases related to Salton Sea Geothermal Field. It includes all input and output files used with the Geothermal Exploration Artificial Intelligence. Input and output files are sorted into three categories: raw data, pre-processed data, and analysis (po...
Moraga, J. et al Colorado School of Mines
Apr 27, 2021
3 Resources
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3 Resources
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Retrofitting a 1960s Split-Level Cold-Climate Home
The U.S. Department of Energy Building America research team Consortium for Advanced Residential Buildings (CARB) partnered with Preferred Builders, a previous CARB partner and builder of the Performance House (DOE 2013) and the owners of a 1960s split-level home in Westport, Conn...
Puttagunta, S. Steven Winter Associates of the Consortium for Advanced Residential Buildings
Apr 27, 2016
3 Resources
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3 Resources
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High-Fidelity Building Emulator
This dataset provides high-fidelity time series data for an emulated commercial office building sited in the Chicago, IL area during a Typical Meteorological Year (TMY). This dataset consists of air-side HVAC measurements and control inputs, and it includes normal operations as w...
Bakker, C. et al Building Technologies Office (BTO)
Jun 15, 2022
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Testing for Controlled Rapid Pressurization
Borehole W1 is a NQ core hole drilled at our test site in Socorro. The rock is rhyolite. Borehole W1 which was used to test gas-gas explosive mixtures is 55 feet deep with casing (pinkish in the drawing) set to 35 feet. The model is a representation of the borehole and the hol...
Knudsen, S. Sandia National Laboratories
Sep 03, 2014
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