Characterization of pore and grain size distributions in porous geological samples-An image processing workflow

An image processing workflow is presented for the characterization of pore and grain size distributions in porous geological samples from X-ray microcomputed tomography (mu CT) and scanning electron microscopy (SEM) images. The pore and grain size distributions of five sandstone samples including Berea, Buff Berea, Nugget, Castlegate, and Bentheimer, and one carbonate sample, Indiana limestone, are extracted using the proposed workflow. Two-dimensional size distributions acquired from SEM images were found to be biased toward smaller sizes misrepresenting the actual 3D distributions. Stereological techniques unfolded the measured 2D size distributions from SEM images to 3D distributions comparable with mu CT results. While larger pores and grains can easily be detected from mu CT and SEM images, the quantification of small-scale heterogeneities is severely influenced by their limits of resolution. We show that microstructural details resolved by SEM can significantly impact the pore and grain size distributions in sandstone and carbonate rock samples. For example, SEM-resolved microporosities in Indiana limestone result in bimodal distributions of pore and grain sizes, whereas mu CT observations exhibit unimodal distributions. The acquired images and processed results are openly available and may be used by researchers investigating image processing, magnetic resonance relaxation or fluid flow simulations in natural rocks. The proposed methodology can be implemented to process mu CT and SEM images of natural rocks as well as other types of porous materials.

Automated summary

The proposed image processing workflow efficiently characterizes pore and grain size distributions in porous geological samples using SEM and mu CT images. Results indicate a bias in 2D size distributions acquired from SEM images, which can be corrected using stereological techniques to provide more accurate 3D distributions comparable with mu CT results. Additionally, microstructural details resolved by SEM significantly impact pore and grain size distributions in sandstone and carbonate rock samples, showing bimodal distributions in SEM-resolved microporosities compared to unimodal distributions observed in mu CT images.