Decoding Rocks: An Assessment of Geomaterial Microstructure Using X-ray Microtomography, Image Analysis and...

Area of Science:

• Geoscience
• Materials Science
• Image Analysis

Background:

• Understanding geomaterial microstructure is crucial for evaluating functional properties and geological history.
• Characterizing granular materials requires detailed analysis of grain properties and spatial distribution.

Purpose of the Study:

• To present a semi-automated statistical protocol for complex 3D characterization of granular material microstructure.
• To detail grain clustering, chemical composition, size, shape, and spatial properties using 44 unique parameters.

Main Methods:

• Utilizing X-ray microtomographic image processing.
• Employing image analysis and statistical multivariate analysis with freeware.
• Applying the protocol to a sandstone sample with localized deformational microstructures.

Main Results:

• Successfully clustered grains into groups based on compositional and geometrical features.
• Identified pervasive and even grain distribution within the sample.
• Revealed organized spatial arrangement and directional trends in grain clusters, indicating microstructural features.

Conclusions:

• The developed statistical approach provides a comprehensive 3D characterization of granular material microstructure.
• The method is applicable to various rock types for tracking microstructural trends.
• This technique enhances the understanding of geomaterial properties and geological history through detailed microstructural analysis.