Development of a new semi analytical model for prediction of bubble point pressure of crude oils
Estimation of bubble point pressure is of primary importance for development of oilﬁeld development strategies such as Enhanced Oil Recovery. Traditional techniques for estimation of this critically important property are often not as accurate as is required and may require extended compositional analyses to be conducted beforehand. In this work, a semi-analytical model for prediction of bubble point pressure is proposed. The model uses temperature–concentration interaction terms to portray the ﬂuid behavior. A comprehensive literature review is conducted ﬁrst to understand the limitations of the currently available models. Based on analytical inputs from theoretical concepts and the study of experimental data a new parametric expression containing exponential temperature–concentration interaction is proposed. A large data set, comprising of 129 crude oil samples of different varieties and geographical origins, is compiled from the existing literature for the calibration of the model, using non-linear regression techniques. The results indicate that the model is more accurate than known techniques for estimation of bubble point pressure. The validity of the model to the experimental data and physical phenomena is veriﬁed. One of the salient features of the present model is accurate computation of bubble point pressure sensitivity with respect to change in crude composition. Thus, the proposed model correctly simulates the experiments such as gas injection swelling tests and bubble point curve determination under different compositions. The results of the present investigation will facilitate strategies for production enhancement activities.