Geostatistical Simulation of Regionalized Pore-Size Distributions Using Min/Max Autocorrelation Factors

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Teaching Aid: Minimum/Maximum Autocorrelation Factors for Joint Simulation of Attributes (2012, methodology): “As pointed out by VargasGuzmán and Dimitrakopoulos (2003), failing to check whether this assumption is applicable or not might lead to unknown errors or inconsistencies (Desbarats and Dimitrakopoulos 2000).”
Block Simulation of Multiple Correlated Variables (2009, methodology): “where B is the variance/covariance matrix of Y(u), a multi-Gaussian RF, and Y (h) is the variogram matrix at lag h. The above derivation of A is equivalent to performing two successive principal component analysis decompositions ( Desbarats and Dimitrakopoulos 2000 ).”
Direct Sequential Co-simulation with Joint Probability Distributions (2010, methodology): “To reproduce joint spatial patterns (given by covariograms and bi-histograms), the following simulation algorithms can be used: sequential multi-Gaussian co-simulation (Verly 1993), multi-Gaussian co-simulation with collocated co-kriging (Almeida and Journel 1994), co-simulation with LU decompositio”
Projection Pursuit Multivariate Transform (2014, methodology): “As this assumption is often unrealistic, MAF provides more robust spatial decorrelation through considering the covariance between variables at h = 0 and another h > 0 lag distance (Desbarats and Dimitrakopoulos 2000; Switzer and Green 1984).”