A surfactant-alternating-gas (SAG) process is a promising enhanced oil recovery (EOR) method for tight oil reservoirs. In this study, an empirical model is developed to predict the dynamic performance of a SAG process including sweep efficiency of multiple types of well patterns, in which major factors of the SAG process are involved, including gas channeling, reservoir heterogeneity, gravity segregation, and the instability of a foam structure. A novel empirical model is proposed to estimate the recovery factor of a SAG process in typical well patterns, which divides the whole area into three parts based on dominate occupation in situ fluids. Estimating the breakthrough time of each area is the key of this model. A new concept pseudomobility ratio is proposed to convert the negative effect of heterogeneity into unfavorable increment of mobility ratio. Numerical simulation studies are introduced to validate the proposed SAG empirical model. The comparison shows that the SAG performance model is highly consistent with the numerical simulation results calculated by cmg. Sensitivity analysis is introduced to study the effects of variables in the SAG process, including the fluid injection rate, slug size, slug proportion, and reservoir heterogeneity. Oil production estimated by the proposed model is also validated with field production data collected from the Ganguyi SAG project in China, and the growth trend of oil production agrees well with the field data. The proposed model provides a fast approach to predict the dynamic performance of SAG flooding in a field scale, which can be used as a tool to evaluate and optimize current operational parameters.

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