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Title: Improved Geothermometry Through Multivariate Reaction-path Modeling and Evaluation of Geomicrobiological Influences on Geochemical Temperature Indicators: Final Report

Abstract

The project was aimed at demonstrating that the geothermometric predictions can be improved through the application of multi-element reaction path modeling that accounts for lithologic and tectonic settings, while also accounting for biological influences on geochemical temperature indicators. The limited utilization of chemical signatures by individual traditional geothermometer in the development of reservoir temperature estimates may have been constraining their reliability for evaluation of potential geothermal resources. This project, however, was intended to build a geothermometry tool which can integrate multi-component reaction path modeling with process-optimization capability that can be applied to dilute, low-temperature water samples to consistently predict reservoir temperature within ±30 °C. The project was also intended to evaluate the extent to which microbiological processes can modulate the geochemical signals in some thermal waters and influence the geothermometric predictions.

Authors:
 [1];  [1];  [1];  [1];  [1];  [1];  [1];  [1]
  1. Idaho National Lab. (INL), Idaho Falls, ID (United States)
Publication Date:
Research Org.:
Idaho National Lab. (INL), Idaho Falls, ID (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1177234
Report Number(s):
INL/EXT-14-33959
DOE Contract Number:  
AC07-05ID14517
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
15 GEOTHERMAL ENERGY; Geothermometry

Citation Formats

Mattson, Earl, Smith, Robert, Fujita, Yoshiko, McLing, Travis, Neupane, Ghanashyam, Palmer, Carl, Reed, David, and Thompson, Vicki. Improved Geothermometry Through Multivariate Reaction-path Modeling and Evaluation of Geomicrobiological Influences on Geochemical Temperature Indicators: Final Report. United States: N. p., 2015. Web. doi:10.2172/1177234.
Mattson, Earl, Smith, Robert, Fujita, Yoshiko, McLing, Travis, Neupane, Ghanashyam, Palmer, Carl, Reed, David, & Thompson, Vicki. Improved Geothermometry Through Multivariate Reaction-path Modeling and Evaluation of Geomicrobiological Influences on Geochemical Temperature Indicators: Final Report. United States. doi:10.2172/1177234.
Mattson, Earl, Smith, Robert, Fujita, Yoshiko, McLing, Travis, Neupane, Ghanashyam, Palmer, Carl, Reed, David, and Thompson, Vicki. Sun . "Improved Geothermometry Through Multivariate Reaction-path Modeling and Evaluation of Geomicrobiological Influences on Geochemical Temperature Indicators: Final Report". United States. doi:10.2172/1177234. https://www.osti.gov/servlets/purl/1177234.
@article{osti_1177234,
title = {Improved Geothermometry Through Multivariate Reaction-path Modeling and Evaluation of Geomicrobiological Influences on Geochemical Temperature Indicators: Final Report},
author = {Mattson, Earl and Smith, Robert and Fujita, Yoshiko and McLing, Travis and Neupane, Ghanashyam and Palmer, Carl and Reed, David and Thompson, Vicki},
abstractNote = {The project was aimed at demonstrating that the geothermometric predictions can be improved through the application of multi-element reaction path modeling that accounts for lithologic and tectonic settings, while also accounting for biological influences on geochemical temperature indicators. The limited utilization of chemical signatures by individual traditional geothermometer in the development of reservoir temperature estimates may have been constraining their reliability for evaluation of potential geothermal resources. This project, however, was intended to build a geothermometry tool which can integrate multi-component reaction path modeling with process-optimization capability that can be applied to dilute, low-temperature water samples to consistently predict reservoir temperature within ±30 °C. The project was also intended to evaluate the extent to which microbiological processes can modulate the geochemical signals in some thermal waters and influence the geothermometric predictions.},
doi = {10.2172/1177234},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Sun Mar 01 00:00:00 EST 2015},
month = {Sun Mar 01 00:00:00 EST 2015}
}

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