Modeling of Gas Condensate Well Performance Using Non-Darcy Flow and Capillary Number Effects by Compositional Method

The objective of this paper was to provide a more accurate prediction of gas condensate well performance by considering near well bore effects. These effects include condensate blockage, capillary number dependence of relative permeability and high velocity (non-darcy) that affect well productivity. Capillary number describes the relative balance of viscous and capillary forces. At relatively low gas flow-rate, the effect of high viscous to capillary force ratio dominates the non-darcy effect by reducing the condensate saturation. In this work, the fully implicit, equation of sate (EOS)-based compositional and one dimensional radial reservoir simulator was applied for performance prediction of a single gas– condensate well. The Peng-Robinson equation of state (PR-EOS) was used and tuned to model the fluid phase behavior based on the experimental data. Change in phase densities and viscosities due to change in pressure and compositions were considered. The effect of skin factor on the calculated gas and condensate flow rates was also investigated. Finally, the production history matching was carried out on the SGF-W4 by genetic algorithm to forecast reservoir performance.

Keywords:

Compositional Method , Gas-Condensate Reservoir , Non-Darcy Flow , Genetic Algorithm , Sarkhoon Gas Field