Exploratory analysis of machine learning methods in predicting subsurface temperature and geothermal gradient of Northeastern United States
Abstract Geothermal scientists have used bottom-hole temperature data from extensive oil and gas well datasets to generate heat flow and temperature-at-depth maps to locate potential geothermally active regions. Considering that there are some uncertainties and simplifying assumptions associated wit...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2021-07-01
|
| Series: | Geothermal Energy |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s40517-021-00200-4 |