Alkali-surfactant-polymer (ASP) flooding is a commercially viable enhanced oil recovery method. The complexity of chemical interactions, multi-phase flow, emulsification, capillary number changes and upscaling issues, especially in highly heterogeneous reservoir, make field designs difficult to extrapolate from coreflood measurements. In this work, two representaions of low interfacial tension conditions in chemical flooding were evaluated to determine the impact of model formulation on scaling-up from lab data to field situations. The first one is a mechanistic model based on interpolation of relative permeability curves parametrized with respect to the local capillary number. The second model requires tracking a thermodynamically stable phase known to exist at water-oil ultralow interfacial tension, namely a microemulsion. To perform this analysis, two sets of chemical coreflooding results were history matched and then the tuned models were utilized for field-scale predictions. For ASP flooding, a sensitivity analysis was implemented to show the importance of microemulsion phase on ASP upscaled (field scale) forecast. In this study, coreflooding experiments were performed using three different crude oils, case I: heavy oil with high acid number, case II: medium oil with high acid number and finally, case III: light oil with very low acid number. Predictions between the two modeling approaches are shown to diverge from each other upon upscaling of core-scale history matched models. This discrepancy is mostly attributed to the need to track a microemulsion phase behavior as well as its properties. Effects are more pronounced for heavier oil with high acid number. The results of this analysis should be useful to constrain field projections of any field design of surfactant-assisted EOR projects. Additionally, this study provides guidelines to understand existing uncertainties in current chemical flooding simulation regarding our ability to accurately predict the results of such a chemical flood design.