Research Geologist
Email:
smordensky@usgs.gov
ORCID:
0000-0001-8607-303X
Location
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Geothermal well data from Southern Methodist University (SMU, 2021) and the U.S. Geological Survey (Sass et al., 2005) were used to create maps of estimated background conductive heat flow across the greater Great Basin region of the western US. The heat flow maps in this data release were created using a process that sought to remove hydrothermal convective influence from predictions of background conductive heat flow. Heat flow maps were constructed using a custom-developed iterative process using weighted regression, where convectively influenced outliers were de-emphasized by assigning lower weights to measurements that are very different from the estimated local trend (e.g., local convective influence). The...
Tags: Basin and Range,
Energy Resources,
Great Basin,
USGS Science Data Catalog (SDC),
conductive heat flow, All tags...
convective heat flow,
geothermal,
heat flow map,
hydrothermal,
quality code,
thermal gradient wells,
trend,
uncertainty, Fewer tags
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Topography provides information about the structural controls of the Great Basin and therefore information that may be used to identify favorable structural settings for geothermal systems. Specifically, local relative topography gives information about locations of faults and fault intersections relative to mountains, valleys, or at the transitions between. As part of U.S. Geological Survey efforts to engineer features that are useful for predicting geothermal resources, we construct a detrended elevation map that emphasizes local relative topography and highlights features that geologists use for identifying geothermal systems (i.e., providing machine learning algorithms with features that may improve predictive...
Categories: Data;
Types: Downloadable,
Map Service,
OGC WFS Layer,
OGC WMS Layer,
OGC WMS Service,
Shapefile;
Tags: Basin and Range,
DEM,
Energy Resources,
Geography,
Great Basin, All tags...
Hydrology,
INGENIOUS,
Mineral Resources,
Structural Geology,
USGS Science Data Catalog (SDC),
detrended elevation,
digital elevation models,
elevation,
geothermal,
regional elevation trend,
topography, Fewer tags
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The data contained herein are five input features (i.e., heat flow, distance to the nearest quaternary fault, distance to the nearest quaternary magma body, seismic event density, maximum horizontal stress) and labels (i.e., where known geothermal systems have been identified) from Williams and DeAngelo (2008) and nine favorability maps from Mordensky et al. (2023). The favorability maps are the untransformed predictions from models resulting from the features and labels used with either the methods presented in Williams and DeAngelo (2008) or the machine learning approaches presented in Mordensky et al. (2023). Each favorability map depicts an estimate of relative favorability with respect to the other locations...
Tags: ANN,
Arizona,
California,
Colorado,
Energy Resources, All tags...
Idaho,
Montana,
Nevada,
New Mexico,
Oregon,
SVM,
USGS Science Data Catalog (SDC),
Utah,
Washington,
Western United States,
Wyoming,
XGBoost,
artificial neural network,
data driven,
data-driven,
eXtreme Gradient Boosting,
feed forward neural network,
geothermal,
geothermal favorability,
geothermal resource assessment,
heat flow,
logistic regression,
machine learning,
magmatism,
multilayer perceptron neural network,
quaternary faults,
seismicity,
stress,
support-vector machine,
weight of evidence,
weight-of-evidence, Fewer tags
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