Water alternating gas (WAG) is a well-known strategy to improve the mobility issues during gas injection. However, WAG was identified still having some challenges during implementation at oilfield with high reservoir heterogeneity and high permeable zones in the reservoir and will cause unfavorable mobility ratio. Enproperties of the selected core samplehancement of WAG (EWAG) using foam and surfactant has been research to solve its issue and has success stories. This paper will describe the work process of EWAG to be Pilot at Malaysian oilfield, focusing on numerical investigation during upscaling process.
Foam treatment has role for gas mobility control, delaying gas breakthrough and diverting gas to unswept zones. Meanwhile, the surfactant was utilized to reduce the IFT between gas and liquid to enable gas dispersion into liquid phase. An in-house foaming surfactant has been developed and used for coreflooding experiment at harsh environment. It was used to generate stable foam in contact with gas and it caused a mobility reduction which was suitable for mobilizing trapped oil and hence improving oil recovery. Coreflood experiment was performed on native core and all experimental results were consolidated and checked for the quality prior model calibration in the reservoir simulator. Once coreflood model was constructed, base case was run using default foam parameters. It aimed initially to test whether the model run smoothly and to observe the matching quality using the default values. Once satisfactory matchings were achieved, the process continued with foam parameters upscaling. During scale-up process the velocity of the fluids and pressure drop were conserved as laboratory data. The important scale-up parameters and the corresponding scale-up ratio were investigated.
Mobility Reduction Factor (MRF) was calculated by dividing average DP for each foam cycle with base differential pressure (DP) in the prior gas injection. MRF values for both lower and higher rate show increasing MRF values. Regardless, these values are lower in lower flowrates sequences compared to ones for higher flowrates. This corresponds to MRF values calculated in the laboratory analysis. Therefore, stronger and more stabilized foam were generated using higher injection rates. Lower and higher flowrates had distinctive set of foam parameters. The acceptable matches for differential pressure, oil, water, and gas were achieved. for lower flowrate.
Based on this study, model was able to capture production trends depicted in the laboratory analysis. The foam parameter set from higher flowrates have more potential for further upscaling and modeling in full-field scale.