A VOI Web Application for Distinct Geothermal Domains: Statistical Evaluation of Different Data Types within the Great Basin

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1 Scopus Citations

Abstract

The Great Basin region contains different domains that have different structural and hydrothermal flow patterns. Depending on the characteristics of these patterns, certain data types may be more successful at detecting hidden geothermal resources. In this paper, we quantitatively evaluate if certain data types are more successful in certain domains. Given different aquifer, strain and structural conditions, we explore which data types statistically reveal positively labeled geothermal sites. We utilize value of information (VOI) metrics to help quantify the reliability of data types to discriminate against "positive" and "negative" labeled geothermal sites. We also evaluate how kernel density estimation can help generalize the statistics that inform VOI, which is necessary given the limited data in geothermal exploration. Except for the Carbonate Aquifer, the highest ranking of the Vimperfect is the Local Structural Setting. Next, the slip and dilation tendency is first for Carbonate Aquifer and second for Central Nevada Seismic Belt and Western Great Basin. For the Carbonate Aquifer, heat flow is has the lowest Vimperfect value compared to the other three domains, which is consistent with the understanding of how heat flow measurements are masked by regional groundwater flow.
Original languageAmerican English
Pages1836-1851
Number of pages16
StatePublished - 2023
EventGeothermal Rising - Reno, Nevada
Duration: 1 Oct 20234 Oct 2023

Conference

ConferenceGeothermal Rising
CityReno, Nevada
Period1/10/234/10/23

NREL Publication Number

  • NREL/CP-5700-87160

Keywords

  • Bayesian analysis
  • Great Basin
  • INGENIOUS
  • value of information

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