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GeoThermalCloud framework for fusion of big data and multi-physics models in Nevada and Southwest New Mexico
Our GeoThermalCloud framework is designed to process geothermal datasets using a novel toolbox for unsupervised and physics-informed machine learning called SmartTensors. More information about GeoThermalCloud can be found at the GeoThermalCloud GitHub Repository. More information...
Vesselinov, V. Los Alamos National Laboratory
Mar 29, 2021
4 Resources
0 Stars
Publicly accessible
4 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
11 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
3 Resources
0 Stars
Publicly accessible
Geochemistry and paleo-geothermal features Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada
This submission contains the geochemistry dataset and paleo-geothermal features (sinter, travertine, tufa) (shapefiles and symbology) used in the Nevada Geothermal Machine Learning project.
A submission linking the full GitHub repository for our machine learning Jupyter Notebooks...
Faulds, J. and Ayling, B. Nevada Bureau of Mines and Geology
Nov 01, 2020
2 Resources
0 Stars
Publicly accessible
2 Resources
0 Stars
Publicly accessible
Potential structures Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada
This submission contains shapefiles, geotiffs, and symbology for the revised-from-Play-Fairway potential structures/structural settings used in the Nevada Geothermal Machine Learning project. Layers include potential structural setting ellipses, centroids, and distance-to-centroid...
Faulds, J. and Coolbaugh, M. Nevada Bureau of Mines and Geology
Feb 20, 2021
3 Resources
0 Stars
Publicly accessible
3 Resources
0 Stars
Publicly accessible
Graph Theory for Analyzing Pair-wise Data: Application to Interferometric Synthetic Aperture Radar Data
Graph theory is useful for estimating time-dependent model parameters via weighted least-squares using interferometric synthetic aperture radar (InSAR) data. Plotting acquisition dates (epochs) as vertices and pair-wise interferometric combinations as edges defines an incidence gr...
Reinisch, E. University of Wisconsin
Jul 28, 2016
1 Resources
0 Stars
Publicly accessible
1 Resources
0 Stars
Publicly accessible
GeoDAWN Northwestern Elko County Nevada EarthMRI Data
This submission includes both the original product resolution (OPR) and LiDAR point cloud (LPC) LiDAR data collected as part of GeoDAWN: Geoscience Data Acquisition for Northwestern Elko County, Nevada.
The USGS Earth Mapping Resources Initiative (EarthMRI) and USGS 3D Elevation ...
National Geospatial Program, U. United States Geological Survey
May 15, 2023
7 Resources
0 Stars
Publicly accessible
7 Resources
0 Stars
Publicly accessible
REopt Lite Geothermal Heat Pump Design Requirements
This document describes the design requirements for the geothermal heat pump (GHP) module being added to the existing REopt Lite web tool. This document describes the purpose, users, and functional requirements to which the modified web tool shall conform. This document will be re...
Olis, D. National Renewable Energy Laboratory
Mar 08, 2021
6 Resources
0 Stars
Publicly accessible
6 Resources
0 Stars
Publicly accessible
GeoDAWN West Central Nevada EarthMRI Data
This submission includes both the original product resolution (OPR) and LiDAR point cloud (LPC) LiDAR data collected as part of GeoDAWN: Geoscience Data Acquisition for Western Nevada.
The USGS Earth Mapping Resources Initiative (EarthMRI) and USGS 3D Elevation Program (3DEP), De...
National Geospatial Program, U. United States Geological Survey
May 15, 2023
7 Resources
0 Stars
Publicly accessible
7 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
6 Resources
0 Stars
Publicly accessible
DASH Slow Strain Rates from Brady Hot Springs Geothermal Field during PoroTomo Deployment Period
This submission contains slow strain rates summed to radians over 30 second intervals [rad/s] derived from horizontal distributed acoustic sensing measurements (DASH) of Brady geothermal field during PoroTomo deployment (2016-Mar-14 to 2016-Mar-26). There is one file correspondin...
Reinisch, E. et al University of Wisconsin
Jun 27, 2018
20 Resources
0 Stars
Publicly accessible
20 Resources
0 Stars
Publicly accessible
Geothermal Reservoir Simulation Results in support of Feasibility Study of Direct District Heating for the Cornell Campus Utilizing Deep Geothermal Energy
This dataset contains input data, code, ReadMe files, output data, and figures that summarize the results of a stochastic analysis of geothermal reservoir production from two potential geothermal reservoirs that were evaluated for the Cornell University Deep Direct-Use project. Th...
Smith, J. and Beckers, K. Cornell University
Oct 29, 2019
10 Resources
0 Stars
Publicly accessible
10 Resources
0 Stars
Publicly accessible