Machine learning for natural resource assessment: An application to the blind geothermal systems of Nevada

By: , and 

Links

Abstract

A study is underway to apply machine learning methods to evaluate natural resource potential. In particular, we are considering the search for blind geothermal systems in Nevada. Beginning with the data and experience from the previous Nevada play fairway analysis project, we are building models in TensorFlow/Keras and gaining experience toward predicting the geothermal resource potential as a probability map. During the first year of this project we have encountered several issues particular to using geological and geophysical data sets with these tools. Through an illustrative example we develop a promising workflow for future use as more data become available and are analyzed.

Study Area

Publication type Conference Paper
Publication Subtype Conference Paper
Title Machine learning for natural resource assessment: An application to the blind geothermal systems of Nevada
Volume 44
Year Published 2020
Language English
Publisher Geothermal Resources Council
Contributing office(s) Geology, Minerals, Energy, and Geophysics Science Center
Description 13 p.
Larger Work Type Book
Larger Work Subtype Conference publication
Larger Work Title Geothermal Resources Council Transactions
First page 920
Last page 932
Country United States
State Nevada
Google Analytic Metrics Metrics page
Additional publication details