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Issue No.12 - Dec. (2012 vol.18)
pp: 2041-2050
Daniela Ushizima , Lawrence Berkeley National Laboratory
Dmitriy Morozov , Lawrence Berkeley National Laboratory
Gunther H. Weber , Lawrence Berkeley National Laboratory
Andrea G.C. Bianchi , Lawrence Berkeley National Laboratory
James A. Sethian , University of California, Berkeley
E. Wes Bethel , Lawrence Berkeley National Laboratory
ABSTRACT
One potential solution to reduce the concentration of carbon dioxide in the atmosphere is the geologic storage of captured CO2 in underground rock formations, also known as carbon sequestration. There is ongoing research to guarantee that this process is both efficient and safe. We describe tools that provide measurements of media porosity, and permeability estimates, including visualization of pore structures. Existing standard algorithms make limited use of geometric information in calculating permeability of complex microstructures. This quantity is important for the analysis of biomineralization, a subsurface process that can affect physical properties of porous media. This paper introduces geometric and topological descriptors that enhance the estimation of material permeability. Our analysis framework includes the processing of experimental data, segmentation, and feature extraction and making novel use of multiscale topological analysis to quantify maximum flow through porous networks. We illustrate our results using synchrotron-based X-ray computed microtomography of glass beads during biomineralization. We also benchmark the proposed algorithms using simulated data sets modeling jammed packed bead beds of a monodispersive material.
INDEX TERMS
Geophysical measurements, Carbon dioxide, Sequestration, Algorithm design and analysis, Information analysis, Microscopy, Image segmentation, microscopy, Reeb graph, persistent homology, topological data analysis, geometric algorithms, segmentation
CITATION
Daniela Ushizima, Dmitriy Morozov, Gunther H. Weber, Andrea G.C. Bianchi, James A. Sethian, E. Wes Bethel, "Augmented Topological Descriptors of Pore Networks for Material Science", IEEE Transactions on Visualization & Computer Graphics, vol.18, no. 12, pp. 2041-2050, Dec. 2012, doi:10.1109/TVCG.2012.200
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