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Foams are commonly used to reduce CO2 emissions in oil production and enhance geological storage. The success of these applications relies on key factors such as foam stability, foamability, and residual gas saturation, all of which are significantly influenced by surfactant concentration. Microfluidic platforms provide an effective way to observe these properties at different times by tracking foam texture. While surfactant concentration is known to modify gas-liquid interface properties and affect foam texture in porous media, the role of surfactant aggregation, particularly in stabilizing thin films between bubbles, remains largely unexplored. In this study, we examine the evolution of foam texture over time at varying surfactant concentrations to assess the influence of surfactant aggregation on foam stability, foamability, and residual gas saturation within a representative porous medium. Surfactant solutions, prepared using cocamidopropyl betaine and brine, were analyzed to determine their critical micelle concentration (CMC) via pyrene fluorescence spectroscopy. CO2 was injected into a microfluidic platform, saturated with brine at 22°C and 170 psi, and featuring a pore structure modeled after carbonate rock. High-resolution images of the foam texture were captured over a 3-hour period using a monochromatic sensor. These images were segmented using machine learning techniques to classify pixels and determine bubble dimensions. The evolution of bubble size and distribution was tracked over time to calculate initial foam volume, coarsening rate, and residual gas saturation at each surfactant concentration. The results were correlated with adsorption and CMC data to estimate foam stability under different adsorption conditions, offering insights into the role of surfactant aggregation in CO2 foam performance.
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