Although principal-component analysis (PCA) has been applied widely to reduce the number of parameters characterizing a reservoir, its disadvantages are well-recognized. A work flow was proposed to integrate cumulative-distribution-function-based PCA (CDF-PCA) and streamline information for assisted history matching on a two-facies channelized reservoir. The CDF-PCA was developed to reconstruct reservoir models by use of only a few hundred principal components. It inherits the advantage of PCA to capture the main features or trends of spatial correlations among properties, and, more importantly, it can properly correct the smoothing effect of PCA.
Introduction
Both object-based and multipoint-statistics-based models generate relatively more geologically realistic channel bodies compared with conventional two-point geostatistics-based techniques.
