Mini Review on the Dynamics and Stability Mechanisms of CO ₂ -Flooding-Produced Crude Oil Foams: Recent Progress and Perspectives

CO2–flooding technology, a significant strategy for enhanced oil recovery (EOR) and geological carbon sequestration, can lead to foamy oil formation during surface gathering due to rapid pressure drops, resulting in reduced metering accuracy and complicating gas–liquid separation. This review systematically investigates the kinetic behavior and stability mechanisms of CO2–induced crude oil foams, focusing on bubble nucleation pathways, growth kinetics, coalescence, and rupture behavior, and analyzes the effects of crude oil viscosity, composition, gas properties, and nanoparticles (NPs) on foam stability. The foam dynamic behavior and stability mechanisms of CO2–flooding-produced fluids are shown to exhibit significant differences compared to aqueous foams and other non–aqueous foams, driven by the complex components in the effluents from CO2 flooding and the intricate flow processes of CO2–flooding produced fluids within the wellbore, pipeline, and separator. Heterogeneous nucleation is identified as the dominant bubble formation mechanism. The synergistic effects of asphaltenes, resins, wax crystals, NPs, and other components may give rise to complex cooperative mechanisms, which exert an incredibly intricate influence on foam stability. Therefore, a systematic evaluation from a multiscale perspective, encompassing microscopic mechanisms, mesoscale generalizations, and macroscopic experiments, is required to fully describe the dynamic behavior and stability mechanisms of foams. Moreover, it is essential to develop more reliable defoaming models to provide more effective guidance for production. Existing defoaming models are primarily based on empirical formulas and often lack a robust analysis of multi–parameter coupling effects on oil–based foams. Advancing future studies require integrating molecular dynamics simulations, quantitative foam characterization experiments, foam dynamic analyses, and AI–driven theoretical frameworks to develop multi–scale predictive models. These models would enable a systematic understanding of foam evolution under varying production conditions, ultimately providing theoretical guidance for optimizing CO2–flooding surface transport infrastructure and process control.