Aiming at the development contradictions in the medium-to-high-water-cut stage of continental—deposited and strongly heterogeneous water—flooded reservoirs, a study on development adjustment schemes was carried out by integrating the dynamic characteristics of flow field intensity and intelligent analysis technology. By constructing a three-dimensional dynamic coupling model of the water-cut evolution field, flow field intensity gradient, and remaining oil occurrence field, a seepage flux calculation system and an intelligent control decision-making system were established. The differences in seepage characteristics between the strongly flooded area in the north and the low-flooded area in the south of the reservoir were analyzed, and a classification method for potential areas based on flow field intensity classification and remaining oil distribution was proposed. A closed-loop management mechanism of “monitoring—diagnosis—optimization—verification” was formed, and an intelligent scheme recommendation system integrating machine-learning algorithms was developed to achieve the coordinated control of intelligent optimization of injection—production parameters, targeted implementation of deep profile control and flooding technology, and dynamic adjustment of well pattern structures. This provides a theoretical basis and engineering practice methods for the fine control of similar reservoirs in the middle and late stages of development.