Abstract
This study applied the Pearson correlation coefficient and principal component analysis as tools for unsupervised qualitative petroleum system evaluation techniques. A total of 252 oil samples (32 features per sample) representative of two Brazilian sedimentary basins (Recôncavo and Potiguar) were used to classify them according to their respective degrees of maturation and origin. The large initial set of variables comprises data on δ13C composition, saturate, aromatic, polar compound fractions, and the techniques reduced biomarkers to the most important variables, maintaining the global pattern of variance. The results were efficient in discriminating different petroleum systems from lacustrine, marine, and mixing sources, as observed in the studied accumulations from the Lower Cretaceous sediments of the Recôncavo and Potiguar basins. The methodology proved to be very useful to vene better characterize the petroleum systems. This methodology can be applied to analyze a large amount of oil samples, using simple software and spending relatively less time.
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