Abstract: To achieve low-carbon oil well production and address the source-load time scale mismatch improve oil recovery efficiency in low-permeability oil wells and provide a more economical energy dispatch scheme. A mixed-integer nonlinear optimization model is developed to minimize system operating costs across day-ahead and real-time time scales. The day-ahead stage conducts 24-hour global optimization at 1-hour intervals to determine the optimal inter-pumping schedule. During the real-time stage, the day-ahead schedule is dynamically adjusted every 10 minutes based on ultra-short-term forecasts of wind power output.Using Gurobi for optimization, a case study is conducted on the production data of 10 wells from the YXX clumped well group in Changqing Oilfield. Results show that compared to day-ahead-only optimization, the proposed dual time-scale approach reduces system costs by 38.48% and grid power usage by 10.94%. Compared to manual inter-pumping, system operating costs decrease by 98.39%, and daily power consumption is reduced by 34.12%. Furthermore, compared to a system without storage, total daily operating costs are reduced by 91.56%.The dual-time-scale scheduling optimization model achieves decarbonized oilfield production and provides a new approach for the green transformation of inter-well pumping extraction.