Predicting the dew point pressure for gas condensate reservoirs: empirical models and equations of state

This paper presents a new empirical model to estimate dew point pressure (DPP) for gas condensate reservoirs as a function of routinely measured gas analysis and reservoir temperature. The proposed model was developed using experimentally measured and collected data of 340 gas condensate samples covering a wide range of gas properties and reservoir temperatures. The new model has an average relative deviation (ARD) of 0.44% and average absolute deviation (AAD) of 7.68% or 346 psia (1 psia=6.894757E−3 mPa). The accuracy of the model has been compared to SRK-EOS, PR-EOS and other correlations. Gas condensate samples from this study as well as from literature have been used to check the validity of the proposed model against EOS simulation. These examples have shown that the model successfully captures the physical trend and that the model is reliable. This model is useful to provide an estimate of the DPP when experimentally measured ones are not available. rrent study also shows that predicting the DPP for gas condensates depends on the EOS(s), the number of pseudo-components and the characterization of the plus fraction. For most of the gas condensates used in this study, a 10–12 pseudo-components of the heptane plus (C7+) fraction resulted in minimum error in calculation of DPP using PR-EOS with Pedersen et al. characterization of the plus fraction.