Abstract: This chapter focuses on one narrow application of mathematical modeling for a very common problem that emerges during the building of kinetic models for oil processing: the composition representation problem and a particular set of methods for solving it. These methods are often grouped together under the umbrella term “molecular reconstruction”. Exponential, normal, beta, gamma distributions, and many more, including even Cauchy distribution, can be obtained through entropy maximization under certain constraints. The first insight into the stochastic reconstruction is the realization that we do know something about the sample. Another framework to model the composition is known as molecular type-homologous series matrix method. Generally speaking, stochastic strategies require more computations, but the difficulty of using them grows slower than for deterministic one. That is part of the reason why the stochastic approach (at least to the best of authors' knowledge) is used more often for heavy fractions.

Cite: Glazov N. , Zagoruiko A.
Molecular Reconstruction of Complex Hydrocarbon Mixtures for Modeling of Heavy Oil Processing
Monography chapter Mathematical Modeling of Complex Reaction Systems in the Oil and Gas Industry. – Wiley., 2024. – C.168-186. – ISBN 9781394220052. DOI: 10.1002/9781394220052.ch5 Scopus OpenAlex

Dates:

Published online:

Jul 26, 2024

Identifiers:

Scopus:	2-s2.0-85205634846
OpenAlex:	W4401011692

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