The gas compressibility factor, also known as Z-factor, plays the determinative role for obtaining thermodynamic properties of gas reservoir. Typically, empirical correlations have been applied to determine this important property. However, weak performance and some limitations of these correlations have persuaded the researchers to use intelligent models instead. In this work, prediction of Z-factor is aimed using different popular intelligent models in order to find the accurate one. The developed intelligent models are including Artificial Neural Network (ANN), Fuzzy Interface System (FIS) and Adaptive Neuro-Fuzzy System (ANFIS). Also optimization of equation of state (EOS) by Genetic Algorithm (GA) is done as well. The validity of developed intelligent models was tested using 1038 series of published data points in literature. It was observed that the accuracy of intelligent predicting models for Z-factor is significantly better than conventional empirical models. Also, results showed the improvement of optimized EOS predictions when coupled with GA optimization. Moreover, of the three intelligent models, ANN model outperforms other models considering all data and 263 field data points of an Iranian offshore gas condensate with R2 of 0.9999, while the R2 for best empirical correlation was about 0.8334

Storage of CO₂ in deep saline aquifers is a promising techniques to mitigate global warming and reduce greenhouse gases (GHG). Correct measurement of diffusivity is essential for predicting rate of transfer and cumulative amount of trapped gas. Little information is available on diffusion of GHG in saline aquifers. In this study, diffusivity of CO₂ into a saline aquifer taken from oil field was measured and modeled. Equilibrium concentration of CO₂ at gas-liquid interface was determined using Henry’s law. Experimental measurements were reported at temperature and pressure ranges of 32–50°C and 5900–6900 kPa, respectively. Results show that diffusivity of CO₂ varies between 3.52–5.98×10⁻⁹ m²/s for 5900 kPa and 5.33–6.16×10⁻⁹ m²/s for 6900 kPa initial pressure. Also, it was found that both pressure and temperature have a positive impact on the measures of diffusion coefficient. Liquid swelling due to gas dissolution and variations in gas compressibility factor as a result of pressure decay was found negligible. Measured diffusivities were used model the physical model and develop concentration profile of dissolved gas in the liquid phase. Results of this study provide unique measures of CO₂ diffusion coefficient in saline aquifer at high pressure and temperature conditions, which can be applied in full-field studies of carbon capture and sequestration projects.