| Title | Derivation of a “thermal conductivity” log out of petrophysical correlations |
|---|---|
| Authors | Gegenhuber |
| Year | 2013 |
| Conference | European Geothermal Conference |
| Keywords | Thermal Conductivity, compressional wave velocity, correlation, thermal conductivity log, petrographic code |
| Abstract | Thermal conductivity is one of the key properties of geothermal studies and other applications, like petroleum geology, applications to geothermal energy, civil engineering applications and hydro-geological studies. Due to difficult measurements of the thermal conductivity in boreholes, in most cases only laboratory values are available. Therefore the knowledge of correlations between the thermal conductivity and other petrophysical properties measurable in wells or from the surface could deliver indirectly thermal conductivity. Our approach was to correlate thermal conductivity with compressional wave velocity starting with magmatic rocks and followed with sedimentary rocks (sandstone). Compressional wave velocity was determined with an ultrasonic laboratory device. At each sample from 3 measurements the mean value was determined. Thermal conductivity was measured using the Tk04 thermal conductivity meter from TeKa (Berlin, Germany) with a half-space line-source (transient method). At each sample from 15 measurements the mean value was determined. Two models are applied in order to formulate the basic structure of a correlation between compressional wave velocity and thermal conductivity: a defect and an inclusions model. The solid mineral composition values are taken from the literature. The types of rock are divided into: granite and gneiss, gneiss respectively granite with higher content of quartz, basalt/gabbro/diorite and sandstone. Groups indicate a petrographic code as a property which controls the correlation. Both models give good correlation of measured data. With the derived equations a calculation of the thermal conductivity out of a sonic log was possible. For verification an example was chosen where cores were taken and thermal conductivity measurements were available. The calculated “thermal conductivity log” fits good to the core data. Summarized it can be said that correlations with both models for the laboratory values worked well for the selected rocks. They show the two important factors that influence the thermal conductivity and the velocity: the effect of mineral composition and cracks/fractures. The calculations of the thermal conductivity from the sonic log with both models worked well. Both models show nearly the same results. The values fit to the measured values from the cores in the laboratory. |