An Improved Correlation of Compressibility Factor Prediction of Variable CO2-Content Condensate Gases

The injection of carbon dioxide (CO2) into gas reservoirs has become an important way to enhance gas recovery and reduce CO2 emissions. Large discrepancies are observed when predicting natural gas compressibility factors with high CO2 content by several well-known empirical correlations. An explicit correlation is proposed to improve the prediction accuracy in the estimation of compressibility factors on condensate gases with variable CO2 contents. The analysis of the results is carried out on the basis of 202 experimental data from 9 various mixtures of natural gases. The results show that relative deviations of compressibility factors predicted by conventional empirical correlations increase with the increase in CO2 mole fraction with an average error of 8%. The average error of the new method is less than 4%. The effect of compressibility factors on the estimations of dynamic reserves is studied and the compressibility factor causes a 3% reduction in dynamic reserves estimation. The proposed correlation has fewer uncertainties and more accurate results than other correlations that involve the iterative process in calculating compressibility factors of natural gases with variable CO2 contents.

Automated summary

Injecting carbon dioxide (CO2) into gas reservoirs is an important technique for enhancing gas recovery and reducing CO2 emissions. Existing empirical correlations for predicting compressibility factors of natural gases with high CO2 content show large deviations. This study proposes an explicit correlation to improve the accuracy in estimating the compressibility factors of condensate gases with varying CO2 contents. By analyzing 202 experimental data from 9 different gas mixtures, it is found that the new correlation has a smaller average error (less than 4%) compared to conventional correlations (8% average error).