محمد سرمدی واله

Interfacial tension of methane-water/brine plays a significant role in the different phases of exploitation and processing of natural gas. Therefore, precise prediction of the such important parameter can lead to a more accurate simulation of various processes in which the IFT of methane-water/brine is involved. In this study, the Genetic Programming (GP) modeling approach is utilized to provide an easy-to-use correlation for estimating IFT. The extensive collected dataset consists of 820 measured data of methane-water/brine IFT, which includes effective parameters on IFT, namely; temperature, pressure, and salinity. The efficiency of the developed model was evaluated through different statistical and graphical analyses. The results demonstrated good performance and superiority of the suggested model compared to some of the best correlations available in the literature.