Abstract

Accurate estimation of thermal conductivity of rocks is of paramount importance for projects such as the development of hot dry rock and the geological storage of nuclear waste. In this paper, 30 granite samples from the Songliao and Gonghe Basins in China were tested by X-ray diffraction, polarizing microscope, and Thermal Conductivity Scanning (TCS) measurements. Different mineral contents determine the thermal conductivity of the rock as a whole. The geometric average model and the harmonic average model have great limitations. Combined with the above two models, a new model is proposed for estimating the thermal conductivity, and results are less different from the measured values and have universal applicability. The relative estimation error on the thermal conductivity calculated by mineral composition is significantly reduced. The accuracy of thermal conductivity calculation can be improved by mineral composition.

Highlights

  • Thermal conductivity is an important thermophysical parameter of rock

  • The thermal conductivity of rock is affected by many factors, including mineral composition, porosity [4,5,6,7,8,9], water content [10,11,12,13,14], temperature and pressure [15,16,17,18,19], etc

  • It can be seen that different types of rocks have different ranges of thermal conductivity, which is closely related to the mineral composition and structure of rocks

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Summary

Introduction

Thermal conductivity is an important thermophysical parameter of rock. Thermal conductivity plays a very important role in many research fields [1,2,3]. These areas require more accurate thermal conductivity. The thermal conductivity of rock is affected by many factors, including mineral composition, porosity [4,5,6,7,8,9], water content [10,11,12,13,14], temperature and pressure [15,16,17,18,19], etc. Influenced by Indosinian geological movement, the geosyncline area was strongly uplifted, causing extensive intrusion of Indosinian granite, granodiorite, and other igneous rocks. Influenced by Indosin logical movement, the geosyncline area was strongly uplifted, causing extensive in of Indosinian granite, granodiorite, and other igneous rocks.

Experiment
Range of coincidence
Porosity
Rock Mineral Description
Harmonic Average Model Validation
Relationship between Mineral Composition and Thermal Conductivity
Findings
Conclusions
Full Text
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