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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Casati, R. |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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Kingston, Andrew
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article
Tomographic image analysis and processing to simulate micro-petrophysical experiments
Abstract
We present a description of our departments work flow that utilises X-ray micro-tomography in the observation and prediction of physical properties of porous rock. These properties include fluid flow, dissolution/deposition, fracture mapping, and mechanical processes, as well as measurement of three-dimensional (3D) morphological attributes such as pore/grain size and shape distributions, and pore/grain connectivity. To support all these areas there is a need for well integrated and parallel research programs in hardware development, structural description and physical property modelling. Since we have the ability to validate simulation with physical measurement, (and vice versa), an important part of the integration of all these techniques is calibration at every stage of the work flow. For example, we can use high-resolution scanning electron microscopy (SEM) images to verify or improve our sophisticated segmentation algorithm based on image grey-levels and gradients. The SEM can also be used to obtain sub-resolution porosity information estimated from tomographic grey-levels and texture. Comparing experimental and simulated mercury intrusion porosimetry can quantify the effective resolution of tomograms and the accuracy of segmentation. The foundation of our calibration techniques is a robust and highly optimised 3D to 3D image-based registration method. This enables us to compare the tomograms of successively disturbed (e.g., dissolved, fractured, cleaned,.) specimens with an original undisturbed state. A two-dimensional (2D) to 3D version of this algorithm allows us to register microscope images (both SEM and quantitative electron microscopy) of prepared 2D sections of each specimen. This can assist in giving a multimodal assessment of the specimen.