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Potential structures - Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada

Publicly accessible License 

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 raster.

A submission linking the full GitHub repository for our machine learning Jupyter Notebooks will appear in the related datasets section of this page once available.

Citation Formats

Nevada Bureau of Mines and Geology. (2021). Potential structures - Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada [data set]. Retrieved from https://dx.doi.org/10.15121/1832125.
Export Citation to RIS
Faulds, James, Coolbaugh, Mark. Potential structures - Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada. United States: N.p., 20 Feb, 2021. Web. doi: 10.15121/1832125.
Faulds, James, Coolbaugh, Mark. Potential structures - Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada. United States. https://dx.doi.org/10.15121/1832125
Faulds, James, Coolbaugh, Mark. 2021. "Potential structures - Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada". United States. https://dx.doi.org/10.15121/1832125. https://gdr.openei.org/submissions/1353.
@div{oedi_4556, title = {Potential structures - Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada}, author = {Faulds, James, Coolbaugh, Mark.}, abstractNote = {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 raster.

A submission linking the full GitHub repository for our machine learning Jupyter Notebooks will appear in the related datasets section of this page once available.}, doi = {10.15121/1832125}, url = {https://gdr.openei.org/submissions/1353}, journal = {}, number = , volume = , place = {United States}, year = {2021}, month = {02}}
https://dx.doi.org/10.15121/1832125

Details

Data from Feb 20, 2021

Last updated Feb 9, 2022

Submitted Nov 16, 2021

Organization

Nevada Bureau of Mines and Geology

Contact

James Faulds

775.682.8751

Authors

James Faulds

Nevada Bureau of Mines and Geology

Mark Coolbaugh

Nevada Bureau of Mines and Geology

Research Areas

DOE Project Details

Project Name Applications of Machine Learning Techniques to Geothermal Play Fairway Analysis in the Great Basin Region, Nevada

Project Lead Mike Weathers

Project Number EE0008762

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