Study of Bulk Properties Relation to SARA Composition Data of Various Vacuum Residues Employing Intercriteria Analysis

Twenty-two straight run vacuum residues extracted from extra light, medium, heavy, and heavy crude oils nine different hydrocracked were characterized for their bulk properties SARA composition using four eight fractions (SAR-ADTM) methods. Intercriteria analysis was employed to determine the statistically meaningful relations between data properties. The determined strong modeled computer algebra system Maple NLPSolve with Modified Newton Iterative Method. It found that SAR-ADTM saturates, sum of contents saturates ARO-1 can be predicted residue density, while asphaltene fraction content, asphaltenes, resins correlate softening point residues. strongly negatively correlates Aro-1 fraction, positively Aro-3 fraction. While in residues, is controlled by content H-Oil content. During high severity operation, resulting higher conversion, obtained, which makes it harder more brittle.