PorousMedia / xray_to_pore_size_distribution

The notebook demonstrates the workflow for obtaining pore size distribution from binarized micro-CT images. The general principle involves identifying each pore, estimating the volume of each pore, and ultimately determining the radius of a sphere with an equivalent volume of each pore.

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Augmenting Xray micro-CT data with MICP data for high resolution pore-microstructural and flow modelling of carbonate rocks.

Extracting pore size distribution from xray data.

Lead Invsestigator: Olubukola Ishola (olubukola.ishola@okstate.edu)
Co-Investigator: Javier Vilcaez
Associated Paper: Augmenting Xray micro-CT data with MICP data for high resolution pore-microstructural and flow modelling of carbonate rocks.
DOI:

The notebook demonstrates the workflow for obtaining pore size distribution from binarized micro-CT images. The general principle involves identifying each pore, estimating the volume of each pore, and ultimately determining the radius of a sphere with an equivalent volume of each pore. There is also an option to analyse the sample to see if it is representative.

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The notebook demonstrates the workflow for obtaining pore size distribution from binarized micro-CT images. The general principle involves identifying each pore, estimating the volume of each pore, and ultimately determining the radius of a sphere with an equivalent volume of each pore.

License:MIT License


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Language:Jupyter Notebook 100.0%