The object of this work was to determine whether new information could be obtained by using gel permeation chromatography (GPC) to fractionate asphaltene samples prior to analysis. In particular, GPC elution profiles, elemental analyses, molecular weights by vapor pressure osmometry (VPO), and boiling point distributions of the asphaltenes isolated from the original Athabasca bitumen feed (Feed) and from its total liquid product (TLP) after visbreaking were compared. The analyses showed that for GPC run using chloroform, fractionation was based on size where elemental analyses and boiling point distributions indicated that the earlier eluting fractions were not aggregates of later eluting fractions. The largest TLP asphaltene species were slightly smaller in size (by GPC and VPO) to those in the Feed asphaltenes; the smallest TLP asphaltene species were smaller than those isolated from the Feed asphaltenes and contained material with an initial boiling point of 340 °C despite both vacuum distillation (524 °C cutpoint) and pentane extraction being used during asphaltene preparation. For comparable molecular sizes by GPC and VPO, the TLP asphaltene fractions had lower H/C ratios and so were more aromatic and consisted of higher boiling material than the Feed asphaltene fractions. VPO results and elemental analysis trends confirmed that pentane extraction leaves behind molecules (asphaltenes) on the basis of some combination of size, aromatic content, and polarity. The significance of the various fractions of asphaltene species isolated remains to be evaluated in terms of their contributions to bitumen and heavy oil behavior during both production and thermal processing.

To fully advance our understanding of hydrocarbon conversion chemistry requires powerful analytical methods to qualitatively and quantitatively characterize complex petroleum fractions at the molecular level. In the absence of such tools, an alternative solution is to model the molecular composition of hydrocarbon mixtures with limited analytical data. The objective of this study is to integrate modeling techniques with conventional and advanced petroleum characterization methods to derive the composition of middle distillate fractions at the molecular level. In the present approach, analytical petroleum characterization data are used as input to computationally generate a mixture of representative molecules that mimics the properties of the real sample. The representing molecules are constructed according to coherent chemical/thermodynamic criteria by Monte Carlo sampling of a set of statistical functions assigned to each possible molecular feature. The assembled mixture is built on a large set of chemical species and is further optimized with the principle of Maximum Entropy. The approach is applied to simulating two middle distillates differing significantly in hydrocarbon type composition and origin. The samples are experimentally characterized by standard and advanced analytical methods: density, simulated distillation, elemental analysis, hydrocarbon types/distributions and sulfur compound speciation by two-dimensional gas chromatography with flame ionization detector (GC × GC−FID) and sulfur chemiluminescence detector (GC × GC−SCD), and 13 C nuclear magnetic resonance (NMR), to obtain sufficient information for parameter fitting and model validation. Simulation results showed that the model is capable of generating representative mixtures that reasonably match the actual physical samples in analytical properties and carbon number distributions.