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Title: Cluster analysis as a tool for evaluating the exploration potential of Known Geothermal Resource Areas

Abstract

Although many Known Geothermal Resource Areas (KGRAs) in southeast Oregon and southern Idaho were identified during the 1970s and 1980s, few were subsequently developed commercially. Because of advances since the 1980s, it is possible that some of previously identified KGRAs may now be economically viable prospects. Unfortunately, available characterization data vary widely in accuracy, precision, and granularity, making assessments problematic. Here we present a decision-making procedure that compares test areas against proven resources using principal component analysis (PCA) and cluster identification. The result is a low-cost decision making tool for evaluating potential geothermal development targets and prioritizing exploration efforts.

Authors:
 [1];  [2];  [3];  [1];  [3];  [1];  [2];  [3]
  1. Univ. of Idaho, Moscow, ID (United States). Dept. of Geological Sciences
  2. Idaho National Lab. (INL), Idaho Falls, ID (United States)
  3. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Idaho National Lab. (INL), Idaho Falls, ID (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Geothermal Technologies Office
OSTI Identifier:
1415519
Alternate Identifier(s):
OSTI ID: 1434027; OSTI ID: 1471079
Report Number(s):
INL/JOU-17-42830-Rev000
Journal ID: ISSN 0375-6505; S0375650517302626; PII: S0375650517302626
Grant/Contract Number:  
AC02-05CH11231; AC07-05ID14517
Resource Type:
Published Article
Journal Name:
Geothermics
Additional Journal Information:
Journal Name: Geothermics Journal Volume: 72 Journal Issue: C; Journal ID: ISSN 0375-6505
Publisher:
Elsevier
Country of Publication:
United Kingdom
Language:
English
Subject:
15 GEOTHERMAL ENERGY; 58 GEOSCIENCES; 97 MATHEMATICS AND COMPUTING; KGRAs; Geothermal exploration; Idaho/Oregon; PCA; Cluster analysis; geothermal exploration; cluster analysis

Citation Formats

Lindsey, Cary R., Neupane, Ghanashym, Spycher, Nicolas, Fairley, Jerry P., Dobson, Patrick, Wood, Thomas, McLing, Travis, and Conrad, Mark. Cluster analysis as a tool for evaluating the exploration potential of Known Geothermal Resource Areas. United Kingdom: N. p., 2018. Web. https://doi.org/10.1016/j.geothermics.2017.12.009.
Lindsey, Cary R., Neupane, Ghanashym, Spycher, Nicolas, Fairley, Jerry P., Dobson, Patrick, Wood, Thomas, McLing, Travis, & Conrad, Mark. Cluster analysis as a tool for evaluating the exploration potential of Known Geothermal Resource Areas. United Kingdom. https://doi.org/10.1016/j.geothermics.2017.12.009
Lindsey, Cary R., Neupane, Ghanashym, Spycher, Nicolas, Fairley, Jerry P., Dobson, Patrick, Wood, Thomas, McLing, Travis, and Conrad, Mark. Wed . "Cluster analysis as a tool for evaluating the exploration potential of Known Geothermal Resource Areas". United Kingdom. https://doi.org/10.1016/j.geothermics.2017.12.009.
@article{osti_1415519,
title = {Cluster analysis as a tool for evaluating the exploration potential of Known Geothermal Resource Areas},
author = {Lindsey, Cary R. and Neupane, Ghanashym and Spycher, Nicolas and Fairley, Jerry P. and Dobson, Patrick and Wood, Thomas and McLing, Travis and Conrad, Mark},
abstractNote = {Although many Known Geothermal Resource Areas (KGRAs) in southeast Oregon and southern Idaho were identified during the 1970s and 1980s, few were subsequently developed commercially. Because of advances since the 1980s, it is possible that some of previously identified KGRAs may now be economically viable prospects. Unfortunately, available characterization data vary widely in accuracy, precision, and granularity, making assessments problematic. Here we present a decision-making procedure that compares test areas against proven resources using principal component analysis (PCA) and cluster identification. The result is a low-cost decision making tool for evaluating potential geothermal development targets and prioritizing exploration efforts.},
doi = {10.1016/j.geothermics.2017.12.009},
journal = {Geothermics},
number = C,
volume = 72,
place = {United Kingdom},
year = {2018},
month = {1}
}

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    journal, November 2019


    Characterization of Semnan thermal springs using principal component analysis and geochemical inverse modeling
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