Filter-Based Classification of Training Image Patterns for Spatial Simulation |
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| Authors: | Tuanfeng Zhang Paul Switzer and Andre Journel |
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| Institution: | (1) Department of Geological and Environmental Sciences, Stanford University, California, 94305, USA |
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| Abstract: | Multiple-point simulation, as opposed to simulation one point at a time, operates at the pattern level using a priori structural information. To reduce the dimensionality of the space of patterns we propose a multi-point filtersim algorithm that classifies structural patterns using selected filter statistics. The pattern filter statistics are specific linear combinations of pattern pixel values that represent directional mean, gradient, and curvature properties. Simulation proceeds by sampling from pattern classes selected by conditioning data. |
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| Keywords: | multiple-point simulation geostatistics data conditioning multiple grids |
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