This thesis focuses on the numerical simulation of Low-Tension-Gas (LTG) process, that involves the injection of surfactant and gas to generate and propagate foam for mobility control, and to mobilize the residual oil to waterflood by reducing the interfacial tension between oil and water. This EOR process, is an alternative to surfactant-polymer process and is applicable to challenging conditions including tight formations, high temperature and high salinity reservoirs where polymer implementation is not feasible due to physical and/or economic constraints. In this study, the experimental data used for numerical simulation involve tight carbonate rock with high formation salinity.

For the numerical simulation study, a LTG model developed by the Uni- versity of Texas at Austin and incorporated into the compositional equation- of-state CMG/GEM simulator is utilized. The model includes the modeling of IFT reduction, surfactant partitioning, relative permeability, foam, and ad- sorption.

In some case, a numerical simulation model may involve a large number of uncertain parameters, which often exceeds the experimental data available. Hence, there may exist more than one combination of the parameters that provide a good agreement between the model and the experiments. Therefore, a numerical simulation study is undertaken in order to develop a methodology for determining the LTG model parameters through a series of simulations and data-fitting of strategically selected experimental data to reduce the non- uniqueness of the problem while preserving the physics of the process.

Low capillary number water-oil relative permeability parameters are determined through matching of waterflood experimental data, which is a pre- liminary procedure of LTG flooding. In addition, the reference foam mobility reduction factor, the dry-out function, and the gas relative permeability curve are estimated through matching of foam quality tests. Thereafter, a sensitivity analysis of the remaining uncertain parameters is performed to investigate the significance of the parameters on the oil recovery and pressure drop. Data- fitting of the LTG flood experimental data is then performed to determine es- timations for the rest of the parameter space, including surfactant adsorption, dispersivity, intermediate capillary number and associated oil-water relative permeability curves, oil-gas curvature, and the rest of the foam parameters.

In conclusion, this thesis provides a methodology for estimating rela- tive permeability, foam strength, adsorption and dispersivity parameters for LTG simulation. These findings will be proven useful for understanding LTG flooding behavior in EOR processes.