CO2 foam flooding is a promising technique for improving reservoir sweep efficiency and enhancing oil recovery. Effective use of CO2 foam flooding requires a thorough understanding of the foam transport phenomenon in porous media, which is instrumental in selecting surfactants for different reservoirs. Consequently, extensive screening of commercially available chemicals is required for developing viable CO2 foam formulations. Unfortunately, quantification of the transport phenomenon of surfactant stabilized foams in porous media is difficult and requires time-consuming and costly imaging techniques. Therefore, the development of simple, cost-effective, and easy-to-operate screening platforms for understanding foam behavior in porous media is highly desirable.
Microfluidic devices are potential candidates for developing such platforms. They have been widely used in biology, biomedical and environmental sciences for decades. However, there are limited studies on the applicability of microfluidic devices as screening platforms for surfactant enhanced oil recovery applications. Besides, fluid transport modeling based on the pressure data obtained from microfluidic experiments is sparsely explored. To address these challenges, Dr. Guoqing Jian, Dr. Ayrat Gizzatov, Mohammed Kawelah, Dr. Zuhair AlYousef, and Dr. Amr Abdel-Fattah, developed a simple and cost-effective method for developing efficient microfluidic devices for rapid screening of CO2 foam surfactants. Their microfluidic devices can be easily assembled and recycled for surfactant screening and can reduce the time and cost by at least 90% compared with traditional core flooding processes. It is also the first reported foam modeling study in such microfluidic devices. Their findings could help researchers develop enhanced oil recovery strategies much more efficiently. Their work is currently published in the journal, Applied Energy.
In their approach, the microfluidic device was built on commercially available components and subsequently used to test several surfactant-stabilized CO2 foams. Different factors affecting the steady-state foam strength and foam behaviors such as foam quality, surfactant concentration, and oil fraction content were investigated. The authors also explored the potential use of pressure data for foam modeling purposes. Finally, a texture implicit foam model was developed to determine the foam parameters.
The authors conducted the surfactant screening in two micromodel chips. They observed that the developed microfluidic device could screen different surfactants for CO2 foams in minutes, which is one-tenth of the time if conventional set-ups is used. The effects of the type and concentration of the surfactant, gas flow, chip geometry, injection flow rate, and oil fractional flow on the foam strength were systematically studied, providing a thorough understanding of the foam fluids transport phenomenon. Moreover, estimation of the foam model parameters was possible.
In summary, the study reported the successful development of a high-performance, simple and cost-effective microfluidic device for screening CO2 foam surfactants. The device exhibited several advantages, making it a potential candidate for enhanced oil recovery operations. It required fewer materials to assemble, and the chips could be recycled. Moreover, the approach allowed for a thorough understanding of the foam behavior and different factors affecting the foam strength. The steady-state results were useful in estimating the foam model parameters for modeling purposes. Overall, the microfluidic setup was robust and effective in terms of time and cost. In a statement to Advances in Engineering, the first author, Dr. Guoqing Jian explained that the innovative device will enhance foam mobility and performance in reservoirs and would be viable for different applications like enhanced oil recovery.
Jian, G., Gizzatov, A., Kawelah, M., AlYousef, Z., & Abdel-Fattah, A. (2021). Simply built microfluidics for fast screening of CO2 foam surfactants and foam model parameters estimation. Applied Energy, 292, 116815.