A corresponding states-based method for the estimation of natural gas compressibility factors

In this communication, a corresponding states-based model for the calculation/estimation of the gas compressibility factor (z-factor) of natural gasses is proposed. The method applies the gene expression programming (GEP) algorithm. The parameters of the new model comprise the pseudo-reduced pressure and pseudo-reduced temperature. For assessing the performance and accuracy of the developed model, several statistical and graphical error analyses have been applied simultaneously. Additionally, comparisons have been made between this method and the most widely-used correlations and equations of state (EoS) available in the literature. Various statistical parameters are also used to evaluate the validity and the predictive capability of the newly developed method. Furthermore, the Leverage approach (Williams plot) is used to determine the realm of prediction capability of the new z-factor model and to detect any probable erroneous data points. The results obtained demonstrate that the newly proposed model is more reliable and more effective than the empirical models and EoS methods for prediction of z-factors of natural gasses.