Numerical simulation of crude oil behaviour from chromatographic data

In the aim of predicting oil fields behaviour, petroleum industry attempts to quantify experimental behaviour. The usual determinations of these behaviour, which are difficult and time consuming, may be challenged by a more convenient and fast inverse gas chromatographic approach. Gas chromatographic retention data of selected test solutes are determined and coefficients (descriptors) of the LSER equation of Abraham et al. are calculated for 47 crude oils of different geographical and geological origins. The data set generated is in accord with chemical composition of crude oils. It is used to classify crude oils, to construct QSBR (Quantitative Structure Behavior Relationships) models to predict behaviour and is compared with crude oil polarity parameters. Thus descriptors resulting from applying a solvation model to gas chromatography could provide valuable information for optimisation of operations in oil industry.