Preliminary report on applications of machine learning techniques to the Nevada geothermal play fairway analysis

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Abstract

We are applying machine learning (ML) techniques, including training set augmentation and artificial neural networks, to mitigate key challenges in the Nevada play fairway project. The study area includes ~85 active geothermal systems as potential training sites and >12 geologic, geophysical, and geochemical features. The main goal is to develop an algorithmic approach to identify new geothermal systems in the Great Basin region. Major objectives include: 1) integrate ML techniques into the geothermal community; 2) develop open community datasets, whereby all play fairway and ML datasets and algorithms are publicly released and available for modification by various user groups; 3) identify data acquisition targets with high value for future work; 4) identify new signatures to detect blind geothermal systems; and 5) foster new capabilities for characterizing subsurface temperature and permeability. Initially, ML techniques are being applied to the same play fairway datasets and workflow. ML will then be applied to both enhanced and additional datasets, with modification of the PFA workflow to incorporate the new datasets. Finally, ML will be applied to define new workflows using the enhanced and additional datasets. An algorithmic approach that empirically learns to estimate weights of influence for diverse parameters can potentially scale and perform better than the play fairway analysis. Initial work on this project has involved 1) evaluating potential positive and negative training sites, 2) transformation of datasets into formats suitable for ML, and 3) initial development and testing of ML techniques.

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Publication type Conference Paper
Publication Subtype Conference Paper
Title Preliminary report on applications of machine learning techniques to the Nevada geothermal play fairway analysis
Year Published 2020
Language English
Publisher Stanford Geothermal Program
Contributing office(s) Geology and Geophysics Science Center, Geology, Minerals, Energy, and Geophysics Science Center
Description 6 p.
Larger Work Type Book
Larger Work Subtype Conference publication
Larger Work Title Proceedings: 45th workshop on geothermal reservoir engineering
First page 229
Last page 234
Conference Title 45th Workshop on Geothermal Reservoir Engineering 2020
Conference Location Stanford, CA
Conference Date February 10-12, 2020
Country United States
State Nevada
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