CONSTRUCTION OF A MOLECULAR REPRESENTATION OF A COMPLEX FEEDSTOCK BY MONTE-CARLO AND QUADRATURE METHODS

The value of representing a complex petroleum mixture in terms of a sm all (similar to 10-100) number of molecules motivated the development of a novel algorithm for building a representative set of molecular st ructures. This hybrid Monte Carlo-quadrature method represents a molec ule as a collection of molecular attribute building blocks (e.g. numbe r of aromatic rings, number of naphthenic rings, number and length of sidechains, etc.). Each attribute is represented by a probability dist ribution function which can be sampled via Monte Carlo simulation to y ield a large ensemble of representative molecules, the properties of t he ensemble being constrained to match experimentally measured analyti cal data. In order to represent the information contained within these probability distribution functions in a reduced form, a quadrature me thod has been developed for the selection of an optimal small set (sim ilar to 10-20) of molecules. The mole fractions of this small set are further optimized to match experimental data. Both the small and large ensembles are capable of matching a large number of key analytical pr operties for a complex petroleum feedstock.