Statistical correlation between thermal conductivity and wave velocities in rocks

Y. J. Jeong, S. H. Han, K. Y. Kim, Tae Sup Yun

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This study reports experimental results of not only thermal conductivity but also compression and shear wave velocities for wide range of rock samples recovered in Korea. Total 45 rock specimens are gathered to represent the different origins, mineralogy, and density. The divided bar method is implemented to obtain thermal conductivity in steady-state and piezo-transducers at kHz ranges are used to measure wave velocities. Measured values are subjected to multiple-regression and statistical analysis with dominant factors of density, which allows constructing the correlative relationship between thermal conductivity and stiffness. Artificial Neural Network (ANN) which learns relationships between data predicts thermal conductivity of rock based on collected physical properties using nonlinear multiple-regression. The statistical approaches using optimal interpolation help understanding and extending correlated multiple geophysical properties in characterization of rocks.

Original languageEnglish
Title of host publicationISRM International Symposium - 8th Asian Rock Mechanics Symposium, ARMS 2014
Editors Kaneko, Kodama, Shimizu
PublisherInternational Society for Rock Mechanics
Pages372-378
Number of pages7
ISBN (Electronic)9784907430030
Publication statusPublished - 2014 Jan 1
Event8th Asian Rock Mechanics Symposium, ARMS 2014 - Sapporo, Japan
Duration: 2014 Oct 142014 Oct 16

Other

Other8th Asian Rock Mechanics Symposium, ARMS 2014
CountryJapan
CitySapporo
Period14/10/1414/10/16

Fingerprint

statistical correlation
thermal conductivity
wave velocity
Thermal conductivity
Rocks
rocks
rock
multiple regression
regression analysis
compression waves
Mineralogy
Korea
Shear waves
mineralogy
transducer
Regression analysis
statistical analysis
artificial neural network
S waves
interpolation

All Science Journal Classification (ASJC) codes

  • Geophysics
  • Geochemistry and Petrology

Cite this

Jeong, Y. J., Han, S. H., Kim, K. Y., & Yun, T. S. (2014). Statistical correlation between thermal conductivity and wave velocities in rocks. In Kaneko, Kodama, & Shimizu (Eds.), ISRM International Symposium - 8th Asian Rock Mechanics Symposium, ARMS 2014 (pp. 372-378). International Society for Rock Mechanics.
Jeong, Y. J. ; Han, S. H. ; Kim, K. Y. ; Yun, Tae Sup. / Statistical correlation between thermal conductivity and wave velocities in rocks. ISRM International Symposium - 8th Asian Rock Mechanics Symposium, ARMS 2014. editor / Kaneko ; Kodama ; Shimizu. International Society for Rock Mechanics, 2014. pp. 372-378
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title = "Statistical correlation between thermal conductivity and wave velocities in rocks",
abstract = "This study reports experimental results of not only thermal conductivity but also compression and shear wave velocities for wide range of rock samples recovered in Korea. Total 45 rock specimens are gathered to represent the different origins, mineralogy, and density. The divided bar method is implemented to obtain thermal conductivity in steady-state and piezo-transducers at kHz ranges are used to measure wave velocities. Measured values are subjected to multiple-regression and statistical analysis with dominant factors of density, which allows constructing the correlative relationship between thermal conductivity and stiffness. Artificial Neural Network (ANN) which learns relationships between data predicts thermal conductivity of rock based on collected physical properties using nonlinear multiple-regression. The statistical approaches using optimal interpolation help understanding and extending correlated multiple geophysical properties in characterization of rocks.",
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Jeong, YJ, Han, SH, Kim, KY & Yun, TS 2014, Statistical correlation between thermal conductivity and wave velocities in rocks. in Kaneko, Kodama & Shimizu (eds), ISRM International Symposium - 8th Asian Rock Mechanics Symposium, ARMS 2014. International Society for Rock Mechanics, pp. 372-378, 8th Asian Rock Mechanics Symposium, ARMS 2014, Sapporo, Japan, 14/10/14.

Statistical correlation between thermal conductivity and wave velocities in rocks. / Jeong, Y. J.; Han, S. H.; Kim, K. Y.; Yun, Tae Sup.

ISRM International Symposium - 8th Asian Rock Mechanics Symposium, ARMS 2014. ed. / Kaneko; Kodama; Shimizu. International Society for Rock Mechanics, 2014. p. 372-378.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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N2 - This study reports experimental results of not only thermal conductivity but also compression and shear wave velocities for wide range of rock samples recovered in Korea. Total 45 rock specimens are gathered to represent the different origins, mineralogy, and density. The divided bar method is implemented to obtain thermal conductivity in steady-state and piezo-transducers at kHz ranges are used to measure wave velocities. Measured values are subjected to multiple-regression and statistical analysis with dominant factors of density, which allows constructing the correlative relationship between thermal conductivity and stiffness. Artificial Neural Network (ANN) which learns relationships between data predicts thermal conductivity of rock based on collected physical properties using nonlinear multiple-regression. The statistical approaches using optimal interpolation help understanding and extending correlated multiple geophysical properties in characterization of rocks.

AB - This study reports experimental results of not only thermal conductivity but also compression and shear wave velocities for wide range of rock samples recovered in Korea. Total 45 rock specimens are gathered to represent the different origins, mineralogy, and density. The divided bar method is implemented to obtain thermal conductivity in steady-state and piezo-transducers at kHz ranges are used to measure wave velocities. Measured values are subjected to multiple-regression and statistical analysis with dominant factors of density, which allows constructing the correlative relationship between thermal conductivity and stiffness. Artificial Neural Network (ANN) which learns relationships between data predicts thermal conductivity of rock based on collected physical properties using nonlinear multiple-regression. The statistical approaches using optimal interpolation help understanding and extending correlated multiple geophysical properties in characterization of rocks.

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Jeong YJ, Han SH, Kim KY, Yun TS. Statistical correlation between thermal conductivity and wave velocities in rocks. In Kaneko, Kodama, Shimizu, editors, ISRM International Symposium - 8th Asian Rock Mechanics Symposium, ARMS 2014. International Society for Rock Mechanics. 2014. p. 372-378