Enhancing refinery heavy oil fractions analytical performance through real-time predicative modeling.

This study introduces a suite of robust models aimed to advance the determination of physiochemical properties in heavy oil refinery fractions. By integrating real-time analytical technique inside the refinery analysis, we have developed a single analyzer capable of employing six partial least square regression equations. These designed models enable to provide real-time prediction of critical petroleum properties, such as sulfur content, micro carbon residues (MCR), asphaltene content, heating value, and the concentrations of nickel and vanadium metals.