In order to study the effect of the micro‐CT scan resolution and size on the accuracy of upscaled digital rock property estimation of core samples Bentheimer sandstone images with the resolution varying from 0.9 μm to 24 μm are used. We statistically show that the correlation length of the pore‐to‐matrix distribution can be reliably determined for the images with the resolution finer than 9 voxels per correlation length and the representative volume for this property is about 153 correlation length. Similar resolution values for the statistically representative volume are also valid for the estimation of the total porosity, specific surface area, mean curvature, and topology of the pore space. Only the total porosity and the number of isolated pores are stably recovered, whereas geometry and the topological measures of the pore space are strongly affected by the resolution change. We also simulate fluid flow in the pore space and estimate permeability and tortuosity of the sample. The results demonstrate that the representative volume for the transport property calculation should be greater than 50 correlation lengths of pore‐to‐matrix distribution. On the other hand, permeability estimation based on the statistical analysis of equivalent realizations shows some weak influence of the resolution on the transport properties. The reason for this might be that the characteristic scale of the particular physical processes may affect the result stronger than the model (image) scale.

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We present analysis of sandstone micro-CT scans obtained with different resolution. We show that use of fine resolution (about 1 micrometer per voxel) do not provide valuable information about the core structure and for the pore surface analysis and makes the sample nonrepresentative even for porosity estimation. Scans with resolution of 3–5 μm per voxel allow to get statistically reliable estimates of the reciprocal pore-to-core distribution, topological properties of the pore space and transport properties of the sample. Using this information one can reconstruct the macroscopic model of poroelastic media.

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