The inherent complexity of petroleum fractions makes molecular reconstruction an essential element to make use of advanced kinetic models in the petrochemical industry, in particular when sulfur compounds need to be accounted for. Therefore, we have developed, a method based on Shannon entropy maximization that can reconstruct the molecular composition of vacuum gas oils and atmospheric gas oils including sulfur compounds even if only a limited amount of global information is provided. Unique in this work is that the results of the reconstruction are compared with analytically determined compositions obtained using comprehensive 2D gas chromatography coupled to a Flame Ionization Detector and a selective Sulfur Chemiluminescence Detector next to the global properties such as boiling point curves and densities. The reconstructed carbon number distribution for global groups (n-paraffins, i-paraffins, naphthenes, and aromatics) and distribution of the sulfur compounds show a good agreement with the analytical data with a maximum standard deviation of 1% or less. Essential is that the molecular library that is used to represent the feedstocks is based on a sufficiently large database of extensively characterized feedstocks. Acquiring the detailed molecular composition of the sulfur-containing compounds could only be done accurately if next to classical commercial indices such as boiling points of a distillation curve, the specific density, and the PINA mass fractions, the total amount of sulfur and aromatic sulfur were specified.

Molecular reconstruction of hydrocarbon and sulfur-containing compounds in atmospheric and vacuum gas oils

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ACS Fall 2022

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