Data-constrained characterization of sandstone microstructures with multi-energy X-ray CT

11th International Conference on X-ray Microscopy

Yang, Y.S.^1 ; Tulloh, A.^1 ; Chen, F.^1 ; Liu, K.Y.^2 ; Clennell, B.^2 ; Taylor, J.^3

CSIRO Materials Science and Engineering, Locked Bag 33, Clayton, VIC 3169, Australia^1

CSIRO Earth Science and Resource Engineering, PO Box 1130, Bentley, WA 6102, Australia^2

CSIRO EResearch and Computational and Simulation Sciences, GPO Box 664, Canberra ACT 2601, Australia^3

关键词: Accurate prediction;    Boltzmann distribution;    Compositional distribution;    Constrained non-linear optimizations;    Linear absorption coefficient;    Microscopic distribution;    Multi-energy x-rays;    Sandstone samples;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/463/1/012048/pdf
DOI  :  10.1088/1742-6596/463/1/012048

来源: IOP

【 摘 要 】

A data-constrained non-linear optimization approach has been developed to characterize microscopic distributions of mineral phases and pores in a sandstone sample using X-ray CT data sets acquired at 35keV and 45keV beam energies as constraints. The approach minimizes discrepancy between the expected and measured linear absorption coefficients and maximizes Boltzmann distribution probability. It enables integration of both the 3D X-ray CT data-constraints and global level information, and leads to more accurate predictions of microscopic 3D compositional distributions in material samples. Permeability simulations and comparisons with experimentally measured porosity indicate that DCM characterisation agrees reasonably with experimental observations. However, segmentation of CT images leads to under-estimation of porosity and permeability.