The Ghareb Formation in the Yamin Plain has been selected as the candidate formation for the deep geological storage of radioactive waste in Israel. This necessitated a comprehensive investigation of its petrophysical, mechanical, mineralogical, and thermal properties to assess its suitability. Key criteria for such a repository include very low permeability to prevent hazardous waste leakage to the aquifer, high mechanical stability to support long-term storage, chemical inertness to avoid interactions with the isolated waste materials, and high thermal conductivity to facilitate heat dissipation through the host rock to the surface. Our study focused on evaluating the petrophysical, mechanical, and thermal conductivity properties of the formation.
The results reveal significant variability in these properties, influenced by factors such as porosity, mineralogy, and rock structure. We focus this presentation on the thermal conductivity as it’s high variability cannot be explained by depth or density alone, and existing thermal conductivity models fail to fully capture its complexity. Conventional models typically rely on mineralogical composition and porosity, or empirical correlations tailored to specific lithologies, yet they do not adequately explain the observed variations in thermal conductivity as encountered in the case of the Ghareb formation.
To address this limitation, we developed a predictive model that integrates the three primary factors influencing thermal conductivity: mineralogy, porosity, and rock structure. The model builds upon the Wiener parallel model, incorporating mineral composition and porosity while also integrating the seismic velocity ratio (Vs/Vp) to account for the rock microstructure. This approach significantly improves predictive accuracy, enabling more reliable thermal conductivity estimates across diverse lithologies. The proposed model serves as a valuable tool for underground engineering applications, particularly in geological repositories and other subsurface projects requiring precise thermal characterization.