Abstract
Clay rock formations are considered as host rocks for underground radioactive waste repositories. Reliable predictions of diffusive transport heterogeneity are critical for assessing the sealing capacity of argillaceous rocks. The predictive power of numerical approaches to flow field analysis and radionuclide migration depends on the quality of the underlying pore network geometry. Both sedimentary and diagenetic complexity are controlling factors.In this study, we demonstrate a cross-scale approach to reconstruct the pore network geometries of the sandy facies of the Opalinus Clay rock. We identified diagenetic and sedimentary subfacies components based on the concentration of diagenetic carbonates and sulfides and grain size variability, and quantified their pore size distributions and pore network geometries. A viable approach for use in transport modeling is to combine μ-CT data segmentation followed by filling the resulting volumes with representative pore network geometries based on FIB-SEM data. The resulting generalized pore network geometries are applied in digital rock models to calculate effective diffusivities, using a combined upscaling workflow for transport simulations from nanometer to micrometer scales.Positron emission tomography (PET) diffusion experiments validated the transport simulation results. We introduced a statistical treatment of the PET and μ-CT tomographic datasets based on the spatial variability of both PET tracer concentrations and rock density. The analyzed effective diffusivities confirmed the numerical results.This study illustrates three important steps in migration analysis: (i) a workflow of general applicability for cross-scale identification of pore network data in argillaceous rocks, (ii) application of the pore network data for the numerical analysis of diffusive transport, and (iii) validation of numerical results via combined PET - μ-CT diffusion experiments. Although the conceptual approach is not feasible for large numbers of samples, it opens up a strong potential for generalization: the validated results of effective diffusivities can now be easily used in a variety of segmented geometries. This allows to efficiently test upscaling concepts for the continuum scale on this basis.
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