Predictive correlations for thermal upgrading of petroleum residues

• Correlative models for thermal conversion of petroleum residues.
• Six operating variables and feed characteristics are employed.
• A wide range of operational conditions and feed types are covered.
• Distillate quality reflected by the sulfur content and heavy gas oil fraction.
• Trends of the correlation models are discussed.

Predictive correlations are presented for thermal conversion of petroleum residues employing a large number of data points obtained from the literature. The proposed correlations include equations adopted in terms of three operating variables of temperature, reaction time, and pressure and three main characteristics of a residuum including API, sulfur content, and CCR to predict upgrading conversion, liquid yield, gas yield, sulfur content of the liquid product, and yield of heavy gas oil. The expressions employed in these correlations were carefully chosen from a large group of functions with a minimum number of regression variables. The trends of the dependent variables in terms of the six independent modeling variables are discussed. Satisfactory statistical results were achieved for all correlation models presented, indicating their applicability to different types of residues over a wide range of operating conditions.