Digital rock physics combines microtomographic imaging with advanced numerical simulations of effective material properties. It is used to complement laboratory investigations with the aim to gain a deeper understanding of relevant physical processes related to transport and effective mechanical properties. We apply digital rock physics to reticulite, a natural mineral with a strong analogy to synthetic open-cell foams. We consider reticulite an end-member for high-porosity materials with a high stiffness and brittleness. For this specific material, hydro-mechanical experiments are very difficult to perform. Reticulite is a pyroclastic rock formed during intense Hawaiian fountaining events. the honeycombed network of bubbles is supported by glassy threads and forms a structure with a porosity of more than 80%. Comparing experimental with numerical results and theoretical estimates, we demonstrate the high potential of in situ characterization with respect to the investigation of effective material properties. We show that a digital rock physics workflow, so far applied to conventional rocks, yields reasonable results for high-porosity rocks and can be adopted for fabricated foam-like materials with similar properties. Numerically determined porosities, effective elastic properties, thermal conductivities and permeabilities of reticulite show a fair agreement to experimental results that required exeptionally high experimental efforts.

<p>Microtomographic imaging techniques and advanced numerical simulations are combined by digital rock physics (DRP) to obtain effective physical material properties. The numerical results are typically used to complement laboratory investigations with the aim to gain a deeper understanding of physical processes related to transport (e.g. permeability and thermal conductivity) and effective elastic properties (e.g. bulk and shear modulus). The present study focuses on DRP and laboratory techniques applied to a rock called reticulite, which is considered as an end-member material with respect to porosity, stiffness and brittleness of the skeleton. Classical laboratory investigations on effective properties, such as ultrasonic transmission measurements and uniaxial deformation experiments, are very difficult to perform on this class of high-porosity and brittle materials.</p><p>Reticulite is a pyroclastic rock formed during intense Hawaiian fountaining events. The open honeycombed network has a porosity of more than 80 % and consists of bubbles that are supported by glassy threads. The natural mineral has a strong analogy to fabricated open-cell foams. By comparing experimental with numerical results and theoretical estimates we demonstrate the potential of digital material methodology with respect to the investigation of porosity, effective elastic properties, thermal conductivity and permeability</p><p>We show that the digital rock physics workflow, previously applied to conventional rock types, yields reasonable results for a high-porosity rock and can be adopted for fabricated foam-like materials. Numerically determined effective properties of reticulite are in good agreement with the experimentally determined results. Depending on the fields of application, numerical methods as well as theoretical estimates can become reasonable alternatives to laboratory methods for high porous foam-like materials.</p>

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Over the last 3 decades, Digital Rock Physics (DRP) has become a complementary part of the characterization of reservoir rocks due to the non-destructive testing character of this technique. The use of high-resolution X-ray Computed Tomography (XRCT) has become widely accepted to create a digital twin of the material under investigation. Compared to other imaging techniques, XRCT technology allows a location-dependent resolution of the individual material particles in volume. However, there are still challenges in assigning physical properties to a particular voxel within the digital twin, due to standard histogram analysis or sub-resolution features in the rock. For this reason, high-resolution image-based data from XRCT, transmitted-light microscope, Scanning Electron Microscope (SEM) as well as geological input properties like geological diagenesis, mineralogical composition, sample’s microfabrics, and estimated sample’s porosity are combined to obtain an optimal spatial segmented image of the studied Ruhr sandstone. Based on a homogeneity test, which corresponds to the evaluation of the gray-scale image histogram, the preferred scan sample sizes in terms of permeability, thermal, and effective elastic rock properties are determined. In addition, these numerically derived property predictions are compared with laboratory measurements to obtain possible upper limits for sample size, segmentation accuracy, and a geometrically calibrated digital twin of the Ruhr sandstone. The comparison corresponding gray-scale image histograms as a function of sample sizes with the corresponding advanced numerical simulations provides a unique workflow for reservoir characterization of the Ruhr sandstone.