1887

Abstract

Summary

Stochastic simulation of complex geology is addressed through discrete wavelet transformation (DWT) that handles multiscale spatial characteristics in datasets and training images. The simulation of the proposed approach is performed on the frequency (wavelet) domain. A multiscale, multipoint simulation algorithm is proposed in this paper in which the scaling image and wavelet images across the scale are simulated jointly. The inverse DWT reconstructs simulated realizations of an attribute of interest in the space domain. The proposed algorithm reduces the computational time required for simulating large domain as compared to spatial domain multipoint simulation algorithm since the simulation is performed in the wavelet domain in which numbers of nodes to be simulated are significantly less as compared to spatial domain nodes. The algorithm is tested with an exhaustive dataset using unconditional simulation in two-dimensional data set. The realisations generated perform well and reproduce the statistics of the training image. The study conducted comparing the spatial domain filtersim multiplepoint simulation algorithm suggests that the proposed multiscale, multipoint algorithm generates equally good realisations at much lower computational cost.

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/content/papers/10.3997/2214-4609.20141810
2014-09-08
2020-02-22
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