15:00 〜 16:00
[S24-P-04] Temperature and heat-flow calculations: about the benefit of well-log based thermal-conductivity profiles
The calculation of temperature and heat-flow-density profiles in boreholes requires reliable values of rock thermal conductivity with depth. We developed a new approach for the indirect determination of thermal conductivity from standard geophysical well logs, which massively enlarges the available databases of subsurface rock conductivities beyond the usual drill core measurements. This approach results in a new set of predictive equations which overcomes the common limitation of empirical equations to specific rock types or to the region for which they were originally developed.
The new set of prediction equations is universally applicable for all major types of sedimentary rocks (clastics, carbonates and evaporites) and allows calculating continuous thermal-conductivity profiles from different combinations of standard geophysical well-logs (i.e. density, hydrogen index, sonic interval transit time, gamma-ray response, photoelectric factor). The combination of three to five well-log parameters results in absolute predictions uncertainties of <15% on a synthetic test data set and of <20% on benchmark laboratory data (Fuchs et al., 2015). However, mean values for geological formations upscaled from laboratory data can be fitted by well logs with uncertainties of approx. 5-7%.
Based on borehole conductivity profiles from various boreholes, we demonstrate the calculation of temperature and heat-flow profiles with absolute errors <3 degC compared to measured temperature logs along boreholes of several kilometers length.
The new set of prediction equations is universally applicable for all major types of sedimentary rocks (clastics, carbonates and evaporites) and allows calculating continuous thermal-conductivity profiles from different combinations of standard geophysical well-logs (i.e. density, hydrogen index, sonic interval transit time, gamma-ray response, photoelectric factor). The combination of three to five well-log parameters results in absolute predictions uncertainties of <15% on a synthetic test data set and of <20% on benchmark laboratory data (Fuchs et al., 2015). However, mean values for geological formations upscaled from laboratory data can be fitted by well logs with uncertainties of approx. 5-7%.
Based on borehole conductivity profiles from various boreholes, we demonstrate the calculation of temperature and heat-flow profiles with absolute errors <3 degC compared to measured temperature logs along boreholes of several kilometers length.