Toward an intelligent approach for determination of saturation pressure of crude oil

Bubble point pressure is a crucial PVT parameter of reservoir fluids, which has a significant effect on oil field development strategies, reservoir evaluation and production calculations. This communication presents a new mathematical model to calculate the saturation pressures of crude oils as a function of temperature, hydrocarbon and non-hydrocarbon reservoir fluid compositions, and characteristics of the heptane-plus fraction. The model was developed and tested using a total set of 130 experimentally measured compositions and saturation pressures of crude oil samples from different geographical locations covering wide ranges of crude oil properties and reservoir temperatures. In-depth comparative studies have been carried out between this new model and five well known predictive models for estimation of saturation pressure of crude oils. The results show that the developed model is more accurate and reliable with the average absolute relative deviation of 4.7% and correlation coefficient of 0.992. In addition, it is shown that the proposed model correctly captures the physical trend of changing the saturation pressure as a function of the input variables. Finally, the applicability domains of the proposed model and quality of the existing experimental data were examined by outlier diagnostics. •An accurate model to calculate the saturation pressure of crude oil is introduced.•Least-square support vector machine (LSSVM) was applied for this purpose.•Comparative studies are carried out between proposed model and the other models.•The validity of the model to the experimental data is successfully verified.•Outlier diagnosis is performed for detection of the probable doubtful data.