Novel mathematical correlation for accurate prediction of gas compressibility factor

Gas compressibility factor is a critical thermodynamic property that is a required input in the estimation of many reservoir fluid properties and reservoir engineering calculations. Experimentally derived values are considered the best, but these are very expensive and time-consuming. In this work, we have developed a new simplified explicit compressibility factor correlation based on a large dataset using a hybrid nonlinear optimization technique. The new model has a correlation coefficient of 0.9997 and very low average relative error and root-mean-square errors. Statistical analysis shows that this new correlation outperforms all of the existing correlations within the range of 0.2 < Ppr <15 and 1.05 < Tpr < 2)