Coso Geothermal Spectral Library for Rocks and Minerals

Cavur, Mahmut; Yu, Yu-Ting; Demir, Ebubekir; Duzgun, H. Sebnem; Pfaff, Katharina; Sabin, Andrew E.; Buck, Cliff

doi:10.15121/1999403

Title: Coso Geothermal Spectral Library for Rocks and Minerals

Dataset
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Abstract

An integrated open mineral spectral library designed to enhance the utility and precision of mineral spectral data for geothermal exploration, developed from a reliable and comprehensive digital dataset for seamless sharing by integrating field data, the USGS spectral library, and pertinent information obtained from Coso geothermal field (Coso) in California. The ASD FieldSpec portable spectrometer was utilized for collecting spectral data, which was subsequently analyzed using the THOR Material Identification tool in ENVI, The Spectral Geologist (TSG) software by CSIRO, and the Fully Constrained Linear Spectral Unmixing algorithm (FCLSU) in MATLAB. Scanning Electron Microscopy (SEM) with a mineralogy-analyzing function was employed to assess the mineral composition of samples, ensuring precise mineralogical analysis. A portable X-ray fluorescence (pXRF) spectrometer was also utilized to gather information on elemental enrichment. A framework for developing spectra data and establishing spectral libraries for various geological cases was proposed within this study. The characteristic spectra of six alteration minerals - alunite, chalcedony, epidote, hematite, kaolinite, and opal - were acquired from Coso samples. The spectral library for the Coso alteration minerals was introduced for further application in academic study or industrial exploration. To browse the Coso Geothermal Spectral data and related figures from spreadsheets: #1 Unzipmore »« less

Authors:

; Yu, Yu-Ting; Demir, Ebubekir; Duzgun, H. Sebnem; Pfaff, Katharina; Sabin, Andrew E.; Buck, Cliff

Publication Date:: 2023-08-23

Other Number(s):: 1528

DOE Contract Number:: EE0008760

Research Org.:: USDOE Geothermal Data Repository (United States); Mining Engineering Department of Colorado School of Mines

Sponsoring Org.:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Geothermal Technologies Program (EE-4G)

Collaborations:: Mining Engineering Department of Colorado School of Mines

Subject:: 15 Geothermal Energy

Keywords:: geothermal; energy; hydrothermal; spectroscopy; spectral database; Coso; geology; Coso geothermal field; GCF; California; spectral library; hydrothermal alteration; alteration minerals; spectral data; elemental enrichment; scanning electron microscopy; X-ray fluorescence; spectrometry

Geolocation:: 36.292405351352,-117.72810665039|36.049347445098,-117.72810665039|36.049347445098,-117.93681758789|36.292405351352,-117.93681758789|36.292405351352,-117.72810665039

OSTI Identifier:: 1999403

DOI:: https://doi.org/10.15121/1999403

Project Location:

Citation Formats


                    Cavur, Mahmut, Yu, Yu-Ting, Demir, Ebubekir, Duzgun, H. Sebnem, Pfaff, Katharina, Sabin, Andrew E., and Buck, Cliff. Coso Geothermal Spectral Library for Rocks and Minerals.  United States: N. p., 2023. 
        Web.  doi:10.15121/1999403.

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                    Cavur, Mahmut, Yu, Yu-Ting, Demir, Ebubekir, Duzgun, H. Sebnem, Pfaff, Katharina, Sabin, Andrew E., & Buck, Cliff. Coso Geothermal Spectral Library for Rocks and Minerals.  United States.  doi:https://doi.org/10.15121/1999403

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                    Cavur, Mahmut, Yu, Yu-Ting, Demir, Ebubekir, Duzgun, H. Sebnem, Pfaff, Katharina, Sabin, Andrew E., and Buck, Cliff. 2023.  
"Coso Geothermal Spectral Library for Rocks and Minerals".  United States.  doi:https://doi.org/10.15121/1999403.  https://www.osti.gov/servlets/purl/1999403. Pub date:Wed Aug 23 00:00:00 EDT 2023

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@article{osti_1999403,

  title        = {Coso Geothermal Spectral Library for Rocks and Minerals},

  author       = {Cavur, Mahmut and Yu, Yu-Ting and Demir, Ebubekir and Duzgun, H. Sebnem and Pfaff, Katharina and Sabin, Andrew E. and Buck, Cliff},

  abstractNote = {An integrated open mineral spectral library designed to enhance the utility and precision of mineral spectral data for geothermal exploration, developed from a reliable and comprehensive digital dataset for seamless sharing by integrating field data, the USGS spectral library, and pertinent information obtained from Coso geothermal field (Coso) in California. The ASD FieldSpec portable spectrometer was utilized for collecting spectral data, which was subsequently analyzed using the THOR Material Identification tool in ENVI, The Spectral Geologist (TSG) software by CSIRO, and the Fully Constrained Linear Spectral Unmixing algorithm (FCLSU) in MATLAB. Scanning Electron Microscopy (SEM) with a mineralogy-analyzing function was employed to assess the mineral composition of samples, ensuring precise mineralogical analysis. A portable X-ray fluorescence (pXRF) spectrometer was also utilized to gather information on elemental enrichment. A framework for developing spectra data and establishing spectral libraries for various geological cases was proposed within this study. The characteristic spectra of six alteration minerals - alunite, chalcedony, epidote, hematite, kaolinite, and opal - were acquired from Coso samples. The spectral library for the Coso alteration minerals was introduced for further application in academic study or industrial exploration. To browse the Coso Geothermal Spectral data and related figures from spreadsheets: #1 Unzip and store the following items in the same folder. 'Contact Probe Data.zip', 'Sample Photos.zip', and 'Coso spectra of higher-certainity minerals.xlsx'. #2 Open 'Coso spectra of higher-certainity minerals.xlsx'. The hyperlinks in the spreadsheet lead to the folders or figures of: spectra .asd file, spectra ASC II file, spectra plots, and sample photos. The spectra data is raw data without splice correction. Spectra .asd files require particular software to open. (These cannot be opened in GIS software such as ArcGIS.) Spectra ASC II files can be opened in a text editor or spread sheet program.},

  doi          = {10.15121/1999403},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {2023},

  month        = {8}

}

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Dataset:

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DOI: https://doi.org/10.15121/1999403

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