Prediction of two-phase compressibility factor in gas condensate reservoirs using genetic algorithm approach

As experimental determination of two-phase compressibility factor in gas condensate reservoirs is expensive/time-consuming, developing a reliable theoretical-based method is vital for this purpose. Here, based on data of constant-volume-depletion experiments, genetic algorithm method was used to develop a correlation for estimating the two-phase compressibility factor in gas condensate reservoirs. The proposed correlation was validated with experimental data of five gas condensate reservoirs, and also compared with most reliable correlation presented in the literature by Rayes et al. (1992). It was found that the proposed correlation by genetic algorithm predicts the experimental values of two-phase compressibility factor with a good accuracy and better than the Rayes et al.'s (1992) correlation.