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On the challenges of greyscale-based quantifications using X-ray computed microtomography. | LitMetric

AI Article Synopsis

  • The study focuses on using greyscale values from μ-CT images of porous rocks, particularly Bentheimer sandstone, for quantitative analyses despite the absence of clear grain and pore resolution.
  • Experiments were conducted to assess errors in greyscale-based calculations of porosity, concentration, and diffusivity, which included comparing low-resolution images of dry and saturated sandstone to high-resolution results.
  • The research ultimately aims to identify major errors in these calculations and offers practical strategies to improve the accuracy of greyscale-based quantifications in porous media studies.

Article Abstract

For X-ray computed microtomography (μ-CT) images of porous rocks where the grains and pores are not fully resolved, the greyscale values of each voxel can be used for quantitative calculations. This study addresses the challenges that arise with greyscale-based quantifications by conducting experiments designed to investigate the sources of error/uncertainty. We conduct greyscale-based calculations of porosity, concentration and diffusivity from various μ-CT experiments using a Bentheimer sandstone sample. The dry sandstone is imaged overtime to test the variation of greyscale values over sequential scans due to instrumentation stability. The sandstone is then imaged in a dry and contrast-agent saturated state at low resolution to determine a porosity map, which is compared to a porosity map derived from segmented high-resolution data. Then the linearity of the relationship between the concentration of a contrast agent and its corresponding attenuation coefficient is tested by imaging various solutions of known concentration. Lastly, a diffusion experiment is imaged at low resolution under dynamic conditions to determine local diffusivity values for the sandstone, which is compared to values derived from direct pore-scale simulations using high-resolution data. Overall, we identify the main errors associated with greyscale-based quantification and provide practical suggestions to alleviate these issues. LAY DESCRIPTION: X-ray computed microtomography (CT) imaging has become an important way to study the pore space of a porous medium. Using segmented images, we can build 3D pore space models for porous media and characterize the morphology and/or run simulations on the models. So, image segmentation is a critical image processing step. However, for low resolution images where image segmentation is not possible, grayscales are directly used for quantifications such as porosity and concentration calculations. Although these types of calculations have been widely accepted and used, the uncertainties and errors associated with grayscale-based quantifications are not fully discussed. Here we specifically design experiments with X-ray CT imaging to address the challenges that arise in grayscale-based quantifications. For instance, in order to validate porosity calculation results from low resolution images (with the help of high attenuating tracer), high resolution images are also acquired, which serve as a benchmark. The errors associated with concentration calculation using grayscale values are also discussed. In addition, numerical simulations using grayscale values are performed on a diffusion experiment images with X-ray CT. The problems that arise in dynamic imaging and the subsequent numerical simulations are discussed. The experiments, calculations and discussions provide a more comprehensive understanding on grayscale-based quantifications and aid in designing better X-ray CT experiments.

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Source
http://dx.doi.org/10.1111/jmi.12805DOI Listing

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