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Testing the correctness of the sequential algorithm for simulating Gaussian random fields
Authors:X.?Emery  author-information"  >  author-information__contact u-icon-before"  >  mailto:xemery@cec.uchile.cl"   title="  xemery@cec.uchile.cl"   itemprop="  email"   data-track="  click"   data-track-action="  Email author"   data-track-label="  "  >Email author
Affiliation:(1) Department of Mining Engineering, University of Chile, Avenida Tupper 2069, Santiago, Chile
Abstract:The sequential algorithm is widely used to simulate Gaussian random fields. However, a rigorous application of this algorithm is impractical and some simplifications are required, in particular a moving neighborhood has to be defined. To examine the effect of such restriction on the quality of the realizations, a reference case is presented and several parameters are reviewed, mainly the histogram, variogram, indicator variograms, as well as the ergodic fluctuations in the first and second-order statistics. The study concludes that, even in a favorable case where the simulated domain is large with respect to the range of the model, the realizations may poorly reproduce the second-order statistics and be inconsistent with the stationarity and ergodicity assumptions. Practical tips such as the lsquomultiple-grid strategyrsquo do not overcome these impediments. Finally, extending the original algorithm by using an ordinary kriging should be avoided, unless an intrinsic random function model is sought after.
Keywords:Sequential Gaussian simulation  Multigaussian distribution  Kriging neighborhood  Screening effect  Ergodic fluctuations
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