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PoroTomo Natural Laboratory Horizontal and Vertical Distributed Acoustic Sensing Data
This dataset includes links to the PoroTomo DAS data in both SEG-Y and hdf5 (via h5py and HSDS with h5pyd) formats with tutorial notebooks for use. Data are hosted on Amazon Web Services (AWS) Simple Storage Service (S3) through the Open Energy Data Initiative (OEDI). Also include...
Feigl, K. et al University of Wisconsin
Mar 29, 2016
20 Resources
1 Stars
Curated
20 Resources
1 Stars
Curated
Imperial Valley Dark Fiber Project Continuous DAS Data
The Imperial Valley Dark Fiber Project acquired Distributed Acoustic Sensing (DAS) seismic data on a ~28 km segment of dark fiber between the cities of Calipatria and Imperial in the Imperial Valley, Southern California. Dark fiber refers to unused optical fiber cables in telecomm...
Ajo-Franklin, J. et al Lawrence Berkeley National Laboratory
Nov 10, 2020
4 Resources
0 Stars
Publicly accessible
4 Resources
0 Stars
Publicly accessible
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
0 Stars
Publicly accessible
4 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
GOOML Kahunanui Data Curation, Historical Modeling, Forecast Modeling, and Genetic Optimization Examples
This submission includes example files and Jupyter Notebooks associated with the Geothermal Operational Optimization using Machine Learning (GOOML) Kahunanui (KHN) fictional geothermal power plant, which uses synthetic data to model a fictional plant. Includes data curation, histo...
Taverna, N. et al Upflow
Jan 30, 2023
10 Resources
0 Stars
In progress
10 Resources
0 Stars
In progress
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
0 Stars
Publicly accessible
6 Resources
0 Stars
Publicly accessible
Brady's Geothermal Field March 2016 Vibroseis SEG-Y Files and UTM Locations
PoroTomo March 2016 Updated vibroseis source locations with UTM locations. Supersedes gdr.openei.org/submissions/824. Updated vibroseis source location data for Stages 1-4, PoroTomo March 2016. This revision includes source point locations in UTM format (meters) for all four Stage...
Feigl, K. University of Wisconsin
Mar 31, 2016
10 Resources
0 Stars
Publicly accessible
10 Resources
0 Stars
Publicly accessible
Brady's Geothermal Field Nodal Seismometer Data
This submission includes links to raw data, field notes, metadata, and p-wave arrival auto-picks from processed data (not provided) from the nodal seismometer array deployed at the PoroTomo Natural Laboratory in Brady's Hot Springs, Nevada during the March 2016 testing. The data i...
Parker, L. University of Wisconsin
Mar 30, 2016
7 Resources
0 Stars
Publicly accessible
7 Resources
0 Stars
Publicly accessible
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
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
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
Soda Lake Geothermal: Raw 3D and 3C Seismic-Reflection Data from 2010 Survey
This dataset contains seismic-reflection records created in 2010 around the Soda Lake geothermal field near Fallon, Nevada. The data was collected by the power plant operator at the time, Magma Energy (CYRQ Energy in 2024). This was a petroleum-industry-quality three-dimensional ...
N. Louie, J. et al University of Nevada Reno
Sep 01, 2010
5 Resources
0 Stars
Curated
5 Resources
0 Stars
Curated
EGS Collab: Modeling and Simulation Working Group Teleconference Series (1-98)
This submission contains the presentation slides and recordings from the first 98 EGS Collab Modeling and Simulation Working Group teleconferences. These teleconferences served three objectives for the project: 1) share simulation results, 2) communicate field activities and resul...
White, M. et al Pacific Northwest National Laboratory
Feb 04, 2020
100 Resources
0 Stars
Publicly accessible
100 Resources
0 Stars
Publicly accessible