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

Description

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.

Resources

Name Format Description Link
57 Geotiff describing distance to centroid of potential structure ellipses used to derive input grids machine learning models for the Nevada Play Fairway study area. UTM NAD 83 zone 11. https://gdr.openei.org/files/1353/potential_structures_disttocentroid_2021.zip
57 Shapefile containing potential structural setting ellipses (revised from NV Play Fairway) used to derive input grids machine learning models for the Nevada Play Fairway study area. UTM NAD 83 zone 11. https://gdr.openei.org/files/1353/potential_structures_ellipses_2021.zip
57 Shapefile containing centroids of potential structures used to derive input grids machine learning models for the Nevada Play Fairway study area. UTM NAD 83 zone 11. https://gdr.openei.org/files/1353/potential_structures_centroids_2021.zip

Tags

  • pull-apart
  • data
  • geospatial
  • geospatial-data
  • distance-to-centroid
  • structure
  • stepover
  • centroids
  • accommodation-zone
  • structural-setting
  • ellipses
  • displacement-transfer-zone
  • fault-termination
  • code
  • fault-intersection
  • raster
  • gis
  • potential-structures
  • machine-learning
  • nevada
  • geothermal
  • energy
  • fault-bend

Topics

Categories