Abstract
Multiple-point geostatistics (MPS) has been proved to be a powerful tool to capture curvilinear structures or complex features in training images. The three-dimensional reconstruction of porous media is of great significance to the research of mechanisms of fluid flow in porous media. However, it is quite difficult to reconstruct the unknown information only by some sparse known data in the process of reconstruction. Therefore, some interpolation methods are used to reconstruct the unknown region for better results. By reproducing high order statistics, MPS allows capturing structures from a training image, then anchoring them to specific model data. A training image is a numerical prior model which contains the structures and relationship existing in realistic models. The experimental results demonstrate that MPS is practical in porous media reconstruction.
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Zhang, T., Du, Y. (2012). Reconstructing Porous Media Using MPS . In: Wang, F.L., Lei, J., Lau, R.W.H., Zhang, J. (eds) Multimedia and Signal Processing. CMSP 2012. Communications in Computer and Information Science, vol 346. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35286-7_43
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DOI: https://doi.org/10.1007/978-3-642-35286-7_43
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