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 language | English |
|---|---|
| Title of host publication | ISRM International Symposium - 8th Asian Rock Mechanics Symposium, ARMS 2014 |
| Editors | Kaneko, Kodama, Shimizu |
| Publisher | International Society for Rock Mechanics |
| Pages | 372-378 |
| Number of pages | 7 |
| ISBN (Electronic) | 9784907430030 |
| Publication status | Published - 2014 Jan 1 |
| Event | 8th Asian Rock Mechanics Symposium, ARMS 2014 - Sapporo, Japan Duration: 2014 Oct 14 → 2014 Oct 16 |
Other
| Other | 8th Asian Rock Mechanics Symposium, ARMS 2014 |
|---|---|
| Country | Japan |
| City | Sapporo |
| Period | 14/10/14 → 14/10/16 |
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All Science Journal Classification (ASJC) codes
- Geophysics
- Geochemistry and Petrology
Cite this
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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 proceeding › Conference contribution
TY - GEN
T1 - Statistical correlation between thermal conductivity and wave velocities in rocks
AU - Jeong, Y. J.
AU - Han, S. H.
AU - Kim, K. Y.
AU - Yun, Tae Sup
PY - 2014/1/1
Y1 - 2014/1/1
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.
UR - http://www.scopus.com/inward/record.url?scp=84962425311&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84962425311&partnerID=8YFLogxK
M3 - Conference contribution
SP - 372
EP - 378
BT - ISRM International Symposium - 8th Asian Rock Mechanics Symposium, ARMS 2014
A2 - Kaneko, null
A2 - Kodama, null
A2 - Shimizu, null
PB - International Society for Rock Mechanics
ER -