With the rapid development of big data and artificial intelligence technology in recent years, various fields have entered the era of intelligence. Automation technology is the foundation for building artificial intelligence and the key to building digital oilfields. For petroleum engineering, although considerable progress has been made in some technical fields such as automated drilling and exploration, there are relatively few explorations in the field of oil ( gas) well completion test related engineering automation. The oil testing and completion engineering process is complex, the well integrity requirements are stricter, the surface equipment is large, the control and management workload requires great labor intensity, the safety risk of on-site personnel is high, and the key engineering data acquisition which mainly relies on manual labor with heavily workloads lagged behind. The data format has not yet been unified, and on-site real-time decision-making still mainly relies on experience. In the face of the complex engineering and the requirements of oil(gas) testing and completion engineering to improve quality and efficiency, it is urgent to form a reliable and comprehensive automation system, establish a remote real-time decision-making information highway from the surface to the underground, from the job site to the rear experts, and promote the oil engineering accelerates into the era of intelligence. In this paper, combined with the actual oil testing projects in Sichuan and Chongqing, it analyzes the current technical problems facing the realization of comprehensive intelligence, and proposes the development direction and prospect of intelligent oil testing technology.