Hi List, I have generated several tens of realisations (in Gaussian "space" using a Normals Scores transform) of 5 variables using joint multivariate collocated sequential gaussian simulation. I am able to validate this simulation by comparing the input data (drillhole composites) to the output data (realisations) by comparison using QQ plots, histograms and statistics (mean, variance and coefficient of variation), and visually examining cross-sections comparing the input and output data. In the case of a simple SGS (and perhaps even a simple CoSGS with Markov Model 1) I can also add to the validation by comparing the variogram model of the input data to the experimental variogram generated from the realisations. In the case of the joint multivariate relaisations, however, I'm unsure whether the experimental variogram of the realisations stands a reasonable chance of reproducing the variogram model of the input data. For example, the 5th and last variable simulation in my mulit-variate sequence is "factorised" by the joint correlations used in the simulation of the preceeding four variables. In laymans terms, I suspect that the experimental variogram of the 5th simulated variable is so far? "removed" or disimilar from the input variogram model (by virtue of the linear combinations between the previous 4 variables) that it may be pointless to attempt this comparison. Has anyone ever attempted this particular validation? If so, do you have any comments? Regards, Colin
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