Application of a New Grain-Based Reconstruction Algorithm to Microtomography Images for Quantitative Characterization and Flow Modeling

Abstract X-ray computed microtomography (XMT) is used for high-resolution, non-destructive imaging and has been applied successfully to geologic media. Despite the potential of XMT to aid in formation evaluation, currently it is used mostly as a research tool. One factor preventing more widespread application of XMT technology is limited accessibility to microtomography beamlines. Another factor is that computational tools for quantitative image analysis have not kept pace with the imaging technology itself. In this paper, we present a new grain-based algorithm used for computer reconstruction and analysis of granular materials (e.g., consolidated or unconsolidated sands) and subsequent network generation. The algorithm differs significantly from other methods because the first step is to extract the fundamental granular structure from a 3D data set, which provides a wealth of information such as grain sizes, aspect ratios, orientations, surface areas, etc. Knowledge of the basic granular structure serves as a foundation for characterizing the void morphology and creating physically representative pore networks. The algorithm is applied to a sample of sandstone from the Frontier Formation in Wyoming, USA, which was imaged using synchrotron XMT. Morphologic and flow-modeling results are presented.