With the ongoing rise in global energy demand, the importance of enhanced oil recovery in oilfield development is becoming increasingly prominent. However, traditional chemical flooding agents face bottlenecks such as poor adaptability to application environments, unclear coupling mechanisms regarding multiple factors, as well as long research and development cycles. This paper systematically discusses the innovative paradigm of oilfield chemical agent development driven by artificial intelligence and proposes four core technological breakthroughs. Firstly, artificial intelligence-empowered molecular simulation technology can reveal the behavior mechanisms of flooding agents under extreme conditions. Secondly, intelligent molecular design using generative adversarial networks and reinforcement learning breaks through the traditional trial-and-error model. Thirdly, the construction of a data-mechanism dual-driven multi-objective optimization model achieves the collaborative prediction of physicochemical properties, economic benefits and environmental friendliness. Lastly, an integrated system of robotic chemist and high-throughput experimental platforms forms a closed-loop system of “artificial intelligence design - automated synthesis - online detection”, yielding a complete ecosystem. The analysis of the current technological development challenges and future development directions reveals that the artificial intelligence-empowered intelligent Research and Development system is expected to promote the transformation of chemical flooding technology toward efficiency, environmental protection and sustainable development, providing a new standard for intelligent oil and gas field development.

In order to elucidate the oil displacement mechanism of micro-emulsions formed by different betaines at pore throats, this study selected three betaine surfactants with different hydrophobic branched chains for a microscopic visualization oil displacement experiment. The interfacial tension, dilational modulus, interactions of oil droplets, and apparent viscosity of the emulsions were measured. Besides, the microscopic oil displacement mechanism and oil displacement effects of different betaines in homogeneous and heterogeneous models were investigated. The results revealed the beneficial interfacial activity and viscosity enhancement effects of the three betaine solutions. With the increase in the branched degree of betaines, the strength of interfacial films and the viscosity enhancement effect decreases. In the homogeneous model, betaine solutions emulsify crude oil into droplets with strong interfacial films. The in-situ plugging effect improves oil recovery and the sweep efficiency in the pore throats, and the remaining oil is mainly in the form of droplets. As the branched degree increases, the strength of the interfacial films and the oil recovery decline. In the heterogeneous model, the plugging effect enhances the pore structure heterogeneity. The three betaine solutions can increase the sweep efficiency but the displacement solutions only migrate along the dominant pathway within the sweep range. As a result, a large amount of isolated cluster residual oil remains, resulting in similar oil recovery efficiency for betaine flooding to that of water flooding in the heterogeneous model.