A SGeMS code for pattern simulation of continuous and categorical variables: FILTERSIM
The new multiple-point geostatistical algorithm (FILTERSIM), which can handle both categorical and continuous variable training images, is implemented in the SGeMS software. The spatial patterns depicted by the training image are first Summarized into a few filter scores; then classified into pattern groups in the filter score space. The sequential simulation approach proceeds by associating each conditioning data event to a closest pattern group using some distance function. A training pattern is then sampled from that group and pasted back onto the simulation grid. Local Multiple-point statistics carried by patterns are captured from the training image, and reproduced in the simulation realizations. Hence complex multiple-scale geological structures call be re-constructed in the simulation grid, conditional to a variety of sub-surface data such as well data and seismic survey. (c) 2008 Elsevier Ltd. All rights reserved.
filter training image multiple-point statistics pattern classification similarity