Simulating Geological Structures Based on Training Images and Pattern Classiﬁcations
P. Switzer, T. Zhang, A. Journel
Department of Geological and Environmental Sciences
CA, 94305, U.S.A
Ph. +01 650 7232879; Fax +01 650 7250979
Local two-dimensional spatial structure, as represented by a training image, can be summarized by a system of ﬁlter scores. Local patterns are then classiﬁed according to these scores. Sequen- tial point-support simulation proceeds by selecting the score class most resembling the local data and then patching a pattern from this class at the simulation location. This procedure can handle both categorical and continuous variable training images. In addition, because the score space has low dimension, computation is eﬃcient. Examples show spatial simulations derived from training images of sand channels and lithofacies.
Keywords: training images, ﬁlters, ﬁlter scores, simulations, spatial uncertainty
In: McRoberts, R. et al. (eds). Proceedings of the joint meeting of The 6th International Symposium On Spatial Accuracy Assessment In Natural Resources and Environmental Sciences and The 15th Annual Conference of The International Environmetrics Society, June 28 – July 1 2004, Portland, Maine, USA.