Well control equipment is one of the key equipment in the process of oil and gas resource development to balance and control formation pressure and prevent blowout accidents. Its safety and stability are crucial for the oil extraction process. In this paper, a dynamic monitoring and diagnosis strategy of well control equipment based on digital twin is proposed to improve the reliability and safety of well control equipment. This paper first introduces the risk assessment method of well control equipment, evaluates, and classifies the possible risks by analyzing the key factors of well control equipment failure. Then, the digital twin platform of well control equipment is constructed to realize real-time monitoring and data acquisition of well control equipment by using virtual model and dynamic data interaction technology. On this basis, the online monitoring and diagnosis strategy of well control equipment is put forward. By analyzing the monitoring data, the operation status of well control equipment is diagnosed and predicted, and the risk is warned in advance. Finally, this paper describes the application cases of the proposed strategy, realizes the online diagnosis and remote control of well control equipment, and improves the efficient operation and maintenance strategy of well control equipment.