Porosity and permeability characterization of coal: A micro-computed tomography study

Hamed Lamei Ramandi*, Peyman Mostaghimi, Ryan T. Armstrong, Mohammad Saadatfar, W. Val Pinczewski

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    209 Citations (Scopus)


    A unique contrast agent technique using X-ray micro-computed tomography (micro-CT) was developed for studying micrometer-sized features in coal. The technique allows for the visualization of coal fractures not visible with conventional imaging methods. A Late Permian medium volatile bituminous coal from Moura coal mine was imaged and the resulting three-dimensional coal cleat system was extracted for fluid flow simulations. The results demonstrate a direct relationship between coal lithotype and permeability, i.e. bright coals offer more permeability than dull coals. However, there was no direct relationship between porosity and permeability for any given lithotype. Scanning electron microscope and energy dispersive spectrometry (SEM-EDS) together with X-ray diffraction (XRD) methods were used for identifying mineral matter at high resolution. After segmentation of the micro-CT image, mineral phase was removed from the segmented data and it was found that permeability was significantly improved by increasing cleat void space and connectivity; suggesting that enhanced recovery methods could target de-mineralization techniques. Overall, only the epigenetic mineral phases in the bright band influenced permeability while lithotype had a stronger impact on permeability than porosity. Coal lithotype and mineralization are important evaluation criteria when considering coal seam gas development sites.

    Original languageEnglish
    Pages (from-to)57-68
    Number of pages12
    JournalInternational Journal of Coal Geology
    Publication statusPublished - 15 Jan 2016


    Dive into the research topics of 'Porosity and permeability characterization of coal: A micro-computed tomography study'. Together they form a unique fingerprint.

    Cite this