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USGS Contributions to the Nevada Geothermal Machine Learning Project (DE-FOA-0001956): Heat Flow Data
This package contains a map surface that depicts the estimated spatial variation of conductive heat flow (mW/m²) in a portion of northern Nevada, the extent of the ‘Nevada Machine Learning Project’ (DE-EE0008762). It was generated using well locations that had an estimated heat flow value from a measured thermal gradient and thermal conductivity, mainly using data from Southern Methodist University, with some additional USGS data. Well data are included along with and a map surface depicting estimated standard error of the heat flow interpolation.
Author(s) |
Jacob DeAngelo |
Publication Date | 2021-11-30 |
Beginning Date of Data | 2021-07-01 |
Ending Date of Data | 2021-07-01 |
Data Contact | |
DOI | https://doi.org/10.5066/P9HRX1LR |
Citation | DeAngelo, J., and Coolbaugh, M.F., 2021, USGS Contributions to the Nevada Geothermal Machine Learning Project (DE-FOA-0001956): Heat Flow Data: U.S. Geological Survey data release, https://doi.org/10.5066/P9HRX1LR. |
Metadata Contact | |
Metadata Date | 2021-11-30 |
Related Publication | There was no related primary publication associated with this data release. |
Citations of these data | No citations of these data are known at this time. |
Access | public |
License | http://www.usa.gov/publicdomain/label/1.0/ |
Harvest Date: 2021-12-01T04:44:28.804Z