Zohreh Farmani - Department of Petroleum Engineering, Faculty of Petroleum, Gas and Petrochemical Engineering, Persian Gulf University, Bushehr, Iran
Danial Farokhian - Department of Petroleum Engineering, Faculty of Petroleum, Gas and Petrochemical Engineering, Persian Gulf University, Bushehr, Iran
Reza Azin - Department of Petroleum Engineering, Faculty of Petroleum, Gas and Petrochemical Engineering, Persian Gulf University, Bushehr, Iran
Mohammad Mallahi - Department of Reservoir Engineering, South Zagros Oil and Gas Production Company, Shiraz, Iran
Manouchehr Vallizadeh - Department of Reservoir Engineering, South Zagros Oil and Gas Production Company, Shiraz, Iran

Relative permeability is an important parameter in modeling, simulation and evaluation of gas injection. In this study, new empirical-mathematical models are developed to predict relative permeability of and water/oil systems in different rock and fluid systems. The Multi-Gene Genetic Programming (MGGP) technique is employed to develop relative permeability equations. The smart correlations presented in this work require capillary number, interfacial tension, API, gas molecular weight and viscosity ratio as extra input variables to improve its precision and accuracy. The new models are evaluated by experimental data extracted from literature and validated by extensive error analysis. The results strongly admit the MGGP approach and high accuracy of developed mathematical correlations.

Relative permeability, Multi-gene genetic programming, Smart correlation, Capillary number