A clear understanding of the main controlling factors for injection and production allocation of polymer flooding is the key to successful differential adjustment for well management in high water cut reservoirs. Generally, sensitivity analysis or design of experiment is used to study the main controlling factors, but the number of adjustment parameters is limited and the optimal results are hard to obtain. Therefore, the paper regards the problem as an inverse problem and studies the controlling factors by combining intelligent optimization and correlation analysis. In general, the correlation between the optimal results of injection and production allocation and each controlling factor is analyzed, and the main controlling factors with the strongest correlation are selected. Results show that injection rate allocation is mainly controlled by pore volume, polymer concentration allocation is mainly controlled by pore volume and formation coefficient, and production rate allocation is mainly controlled by remaining reserves and oil saturation. The case study indicates injection and production adjustment based on the main controlling factors obtains satisfactory development performance while using much less computation cost than that of the intelligent optimization method. The research results provide a good reference for well redistribution adjustment of polymer flooding in large-scale oilfields.