Using geophysical log data to predict the fracture density in a claystone host rock for storing high-level nuclear waste

Previously drilled boreholes of a host rock for a potential nuclear waste repository in Hungary revealed a highly fractured claystone rock body. A crucial step for characterizing the hydrodynamic behavior of such a fractured reservoir is fracture identification and accurate calculation of the fracture density. Although acoustic borehole televiewers provide a reliable base for determining the fracture density, older boreholes usually lack such data. However, conventional borehole geophysical measurements are often accessible in such cases. The aim of this study was to identify any correlations between well log data and fracture density. Multiple linear regression analysis was performed on data from two boreholes penetrating the Boda Claystone Formation in southwest Hungary. The upper section of the BAF-4 borehole was used for training, where the fracture density was estimated with a fit of R 2 = 0.767. The computed regression function predicted the fracture density with high accuracy in both boreholes for all intervals with typical lithological features. However, in some sections where anomalous well log data indicated changes in the lithology, the prediction accuracy decreased. For example, the function underestimated the fracture density in sandy intervals. Article highlights Fracture density of a potential nuclear waste repository predicted by using regression analysis on geophysical logs. Fracture density of a claystone body influenced by resistivity and density. Prediction accuracy may be influenced by grain size, bedding type, and presence of reductive layers.