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Abstract

Today’s technology provides geochemists with numerous statistical techniques, helping them to manipulate, interpret, and deduce results from large amounts of data. Pairwise correlation coefficient and multivariate statistical methods of principal components and cluster analyses were applied to 14 physical and chemical properties of 288 crudes, in order to determine the qualities and their regional distribution patterns in the Orinoco Heavy Oil Belt of Eastern Venezuela.

The initial set of properties (API gravity; kinematic viscosity at 100°F, 140°F, and 210°F; V, Ni, and S content; gross composition; water and crude salinity; and yield below 370°C) were submitted to pairwise comparison and correlation, taking into account their importance in the processes of production, transportation, and refining. It was found that five characteristics (API gravity, kinematic viscosity, V, S, and asphaltene content) are sufficient to characterize the crude qualities in the belt.

Furthermore, the principal components and cluster analyses were applied to the assemblages of these five characteristics for 165 sample localities to classify them into four quality types: A, B, C, and D. Type A denotes the best quality with API gravities greater than 13°, kinematic viscosities at 210°F less than 60 cSt., and sulfur and vanadium contents less than 1.60% and 250 ppm, respectively. Type D represents the extra-heavy crudes with API gravities <8.5°, viscosities at 210°F >300 cSt., sulfur content >3.8%, and vanadium content >400 ppm. Based on this limited number of samples, it has been observed that 10% of the crudes are of Type A, 20% are of Type B, 35% are of Type C, and the remaining 35% are of Type D. These four groups were mapped to show their regional distribution in the entire belt.

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