Heavy Oil fluids contain large concentrations of high molecular weight components, hence large content of the plus fractions, such as C7+.

Different approaches have been developed to characterize the petroleum plus fractions to improve prediction of the pseudo-components properties by equations of state (EOS).

A method is developed, in this work, to split the plus fraction into single carbon numbers (SCN); generating the mole fraction and the respective molecular weight. The developed method is based on the relationships between three parameter gamma distribution (TPG), experimental mole fraction, molecular weight and single carbon number data obtained from literature and industrial contacts. TPG is used to fit the trend of the compositional analysis. The characterized mole distribution as function of single carbon number is generated by integrating the TPG between the limiting molecular weights (LMω). The limiting molecular weights are determined simultaneously during the integration process by fitting the characterized and experimental mole fractions.

The developed method is easy to use. In addition the approach is not dependent on fixed molecular weights assumption that only normal carbon numbers exist in the composition.

There are several correlations generated to predict physico-chemical properties as a function of SCN. Those correlations have been originally developed to work with light oil. The developed approach together along with some of the correlations is tested for heavy oil samples to identify the ranges where they can be applied. Two lumping schemes are used to group the single carbon numbers into pseudo-components. The properties for each pseudo-component, in this work, are used to predict PVT data, constant volume depletion, using Peng-Robinson equation of state, PVTP commercial simulator.

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