Shahrood University of Technology Journal of Mining and Environment 2251-8592 10 1 2019 01 01 A comprehensive benchmark between two filter-based multiple-point simulation algorithms 139 149 1292 10.22044/jme.2018.7335.1584 EN M. Bavand Savadkoohi Faculty of Mining, Petroleum & Geophysics Engineering, Shahrood University of Technology, Shahrood, Iran B. Tokhmechi Faculty of Mining, Petroleum & Geophysics Engineering, Shahrood University of Technology, Shahrood, Iran E. Gloaguen Centre Eau Terre Environnement, Institut National de la Recherche Scientifique, Québec, Canada A.R. Arab-Amiri Faculty of Mining, Petroleum & Geophysics Engineering, Shahrood University of Technology, Shahrood, Iran Journal Article 2018 08 07 Computer graphics offer various gadgets to enhance the reconstruction of high-order statistics that are not correctly addressed by the two-point statistics approaches. Almost all the newly developed multiple-point geostatistics (MPS) algorithms, to some extent, adapt these techniques to increase the simulation accuracy and efficiency. In this work, a scrutiny comparison between our recently developed MPS algorithm, the cross-correlation-wavelet simulation (CCWSIM), and a well-known MPS algorithm, FILTERSIM, is performed. The main motivation to benchmark these two algorithms is that both exploit some digital image processing filters for feature extraction. Indeed, both algorithms compute the similarity (or dissimilarity) between data events in simulation grid and training image in the feature space. In order to compare the accuracy of the algorithms, some statistics such as facies proportion, variogram, and connectivity function are computed. The results obtained reveal an excellent agreement of the CCWSIM realizations with the training image rather than FILTERSIM. Furthermore, on average, the required simulation runtime for CCWSIM is at least 10 times less than that for FILTERSIM. https://jme.shahroodut.ac.ir/article_1292_929a719394bd8a5d70aa48842308c94b.pdf