NUMERICAL-SIMULATION OF CRUDE-OIL BEHAVIOR FROM CHROMATOGRAPHIC DATA

In the aim of predicting oil fields behaviour, petroleum industry atte mpts to quantify experimental behaviour. The usual determinations of t hese behaviour, which are difficult and time consuming, may be challen ged by a more convenient and fast inverse gas chromatographic approach . Gas chromatographic retention data of selected test solutes are dete rmined 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 const ruct QSBR (Quantitative Structure Behavior Relationships) models to pr edict behaviour and is compared with crude oil polarity parameters. Th us descriptors resulting from applying a solvation model to gas chroma tography could provide valuable information for optimisation of operat ions in oil industry.