How to derive thermal conductivities from physical properties of sedimentary rocks
Speaker: Mo-Si Cai Adviser: Tien-Shun Lin
Abstract
Rock thermal conductivity (TC) is an important parameter for understanding subsurface temperature regime and heat flows. Physical properties, measured directly from cores or inferred indirectly from well logs, are commonly used to derive TC using empirical relationships. Rock cores were measured in the laboratory condition, while well logs were measured in in-situ condition in the borehole. Papers of Hartmann et al. (2005) and Fuchs and Forster (2013) utilized optical scanning technique to obtain TC of core, and other physical parameters were measured by multi-sensor core logger (MSCL). They used multi-linear regression (MLR) method to obtain empirical relationships between TC and the parameters. For well log data, parameters of photoelectric factor (Pe), gamma ray (γ), bulk density (ρb), volume fraction of shale (Vsh), sonic interval transit time (∆T) and neutron porosity (ФN) were used to discuss for empirical relationships. Consequently, we can discuss the advantages and disadvantages from these empirical relationships.
For core samples, the results of MLR show the equations of empirical relationships between TC and parameters of density, sonic velocity and porosity. The empirical equations successfully predict TC with small deviation from measured TC (root mean square about 0.15). For well log data, the most important input parameters are the volume fraction of shale, the hydrogen index as well as the sonic interval transit time. The empirical equations successfully predict TC with small deviation from measured TC (root mean square about 0.3). The deviations assessed by rms for well log data are larger, possibly because of variable borehole conditions. Although the rms for core data is smaller, it still contains other effects, such as anisotropy effect. However, there is a need for validation of such an approach for in-situ conditions. Physical properties of cores cannot all be corrected to in-situ conditions. It will cause unreliable interpretation. Well log data were measured in in-situ conditions, so we consider that using well log data to predict in-situ TC is a better approach even if the rock physical properties are indirectly inferred from well logs.
References
Hartmann, A., Rath, V. and Clauser, C., 2005. Thermal conductivity from core and well log data. Int. J. Rock Mech. Min. Sci., 42(7–8), 1042–1055.
Fuchs, S. and Forster, A., 2013. Well log based prediction of thermal conductivity of sedimentary successions: A case study from the North German Basin. Geophys. J. Int., 196 (1), 291–311.