Molecular reconstruction of heavy petroleum residue fractions

Abstract

Molecular reconstruction techniques are methods that allow to create mixtures of molecules from partial analytical data. In this article, a two-step reconstruction algorithm will be presented. The first step, called “stochastic reconstruction” step, assumes that oil mixtures can be described by distributions of structural blocks. The choice of the blocks and distributions is based on expert knowledge. The transformation from a set of distributions into a mixture of molecules is obtained by Monte–Carlo sampling, while a genetic algorithm adjusts the parametric distributions. The second step, termed “reconstruction by entropy maximization”, improves the representativeness of the set of constructed molecules by adjusting their molar fractions. The estimation of these molar fractions is carried out by maximizing an information entropy criterion under linear constraints. The two-step reconstruction algorithm allows to rebuild mixtures that resemble the petroleum fractions more closely than the approaches used previously. To illustrate the approach, the technique is applied to petroleum vacuum residue fractions.