Morphological and Functional Characterisation of Porous Materials

Significant Achievements, Anticipated Outcomes and Future Work

We have now made important steps towards the formation of a "virtual core laboratory", where the structural and flow properties of materials can be predicted via imaging and simulation, rather than through expensive core-flood experiments. A unique catalogue of images of porous materials is being steadily built up. These images, containing up to 8 billion voxels each, originate with data obtained from the X-ray micro-CT facility housed in the department of Applied Mathematics, RSPhysSE, ANU.

Bones, rocks, paper and corals are among the materials that have been imaged at down to 1 micron resolution. Access to the APAC National Facility has enabled the tomographic reconstruction, de-noising and segmentation of these enormous data sets. The final image quality is excellent, suggesting that accurate predicting of static and dynamic properties (NMR response, elasticity, relative and absolute permeability and several others) through simulation should be possible for a wide range of materials.

Computational Techniques Used

Reconstruction of tomographic image data:
Work is complete on the development of an optimised parallel code which reconstructs cone beam tomography data. The code is based on the Feldkamp algorithm and is designed to operate on massive data sets (up to 20483 voxels), which is necessary for the state-of-the-art X-ray CT facility operating at ANU. Additionally, this code is suitable for other CT instruments. The code has been written using the message passing interface, and engages up to 128 processors simultaneously. The code outputs three-dimensional images, typically of porous and multiphase materials. Now that the code has reached production stage, it will be used continuously as long as the ANU X-ray CT facility is operational.

Identifying Phase Distributions:
The tomographic image consists of a cubic array of up to 8 billion reconstructed linear x-ray attenuation coefficient values, each corresponding to a finite volume cube (voxel) of the sample. Beam hardening artefact corrections have been developed for the data sets. Phase separation techniques have also been developed to run on the APAC National Facility. The simplest method is to choose a threshold attenuation which matches a predetermined bulk measurement. In practice this is not a reasonable method, due to peak overlap in the intensity histogram and due to the uncertainty in the bulk measurements. As the intensity values of the phases show distinctive overlap we have developed a more involved approach based on a three step algorithm. The first stage is an nonlinear anisotropic diffusion filter which removes noise while preserving significant features, i.e. the boundary regions between the phases. The second stage applies the unsharp mask sharpening filter. This in itself consists of three operations: (a) blur the original with a smoothing kernel; (b)calculate the mask by subtracting the blurred image from the original; and (c) add the mask, multiplied by a strength factor, to the original. The unsharp mask lacks a theoretical foundation, yet has proven itself in practice to be highly effective at sharpening edges without overly exaggerating the noise. The final stage uses a combination of watershed and active contour methods for segmentation of the gray-scale data. Here we first choose two cutoff intensity values which lie definitely within two distinct phases. Then starting from the boundaries between these two regions on the one hand and the undetermined region on the other, we use an active countours method with a fast marching algorithm to grow in from these boundaries to assign the phase for the voxels in the undetermined region.

Network generation and Medial Axis determination:
Skeletonisation of the image is required to quantify the network morphology of each phase. The size of the data sets mandates the development of parallel algorithms to perform the skeletonisation. We have developed several new algorithms for this purpose as rigorous testing has shown that all previous parallel thinning algorithms do not correctly preserve topology. This method is currently being implemented. We are developing additional codes to calculate other morphological signatures, including the integral geometric Minkowski measured.

Publications, Awards and External Funding

External Funding and Awards

None

Publications

A. Sakellariou, T. J. Sawkins, T. J. Senden and A. Limaye. "X-ray tomography for mesoscale physics applications", Physica A, (accepted), 2004.
C. H. Arns, "A comparison of pore size distributions derived by NMR and Xray-CT techniques", Physica A, (accepted), 2004.
A. P. Sheppard, R. M. Sok and H. Averdunk, "Techniques for Image Enhancement and Segmentation of Tomographic Images of Porous Materials", Physica A, (accepted), 2004.
A. Sakellariou, T. J. Sawkins, T. J. Senden, C. H. Arns, A. Limaye, A. P. Sheppard, R. M. Sok, M. A. Knackstedt, W. V. Pinczewski, L. Inge Berge, P. E. Oren, "Micro-CT facility for imaging reservoir rocks at pore scales", 73rd International Annual Meeting, Society of Exploration Geophysics, Dallas, Paper RCT5-6, October 2003.
C. H. Arns, A. Sakellariou, T. J. Senden, A. P. Sheppard, R. M. Sok, M. A. Knackstedt, W. V. Pinczewski, G. Bunn, "Virtual Core Laboratory: Properties of reservoir rock derived from micro-CT images", 73rd International Annual Meeting, Society for Exploration Geophysics, Dallas, Paper RP2-6, October 2003.
C. H. Arns, A. Sakellariou, T. J. Senden, A. P. Sheppard, R. M. Sok, W. V. Pinczewski, M. A. Knackstedt, "Virtual Core Laboratory: A facility for imaging and modeling petrophysical properties of sedimentary rock", PetroTech2003, New Delhi, India, January 2003.
M. A. Knackstedt, C. H. Arns, A. Limaye, A. Sakellariou, T. J. Senden, A. P. Sheppard, R. M. Sok, W. V. Pinczewski, G. Bunn, "Digital Core Laboratory: Properties of reservoir core derived from 3D images", 2004 Asia Pacific Conference on Integrated Modelling for Asset Management, Kuala Lumpur, Malaysia, Paper SPE 87009, March 2004.