Exploration and practice of intelligent control and operation of oil pipelines

Objective With China’s rising energy demand, oil pipeline mileage and system complexity have increased significantly, posing control challenges. Traditional human-centered control suffers from reliance on personnel skills, limited accuracy in identifying operating conditions, and weak emergency decision-making, hindering pipeline safety and efficiency. To overcome these limitations, an intelligent control system spanning the entire business process is urgently needed to transition from “human control” to “machine control” and fundamentally enhance pipeline safety and efficiency.

Methods The oil pipeline control work was summarized, and a closed-loop business process centered on “perception, cognition, decision-making, and execution” was proposed. Based on the intelligent control paradigm emphasizing “machine control as core, full-domain intelligent control, and normal-state autonomy”, key technologies including large models, mechanism models, deep learning, decision-making reasoning, and automated instruction sets were integrated. An intelligent control system comprising four functional modules—data collection and real-time perception, operation plan compilation and issuance, operating condition identification and analysis, and automatic decision-making and disposal execution—was developed. The intelligence of the control process was realized, and a pilot application was conducted on a typical crude oil pipeline.

Results The intelligent control system was developed to automate the business process, effectively enabling the shift from “human control” to “machine control”. Its pilot application on a crude oil pipeline demonstrated significant reduction in operation plan compilation time, improved accuracy and timeliness in operating condition identification, decreased equipment operation frequency, and enhanced emergency response capabilities. Consequently, control efficiency and safety were markedly improved, and key operational challenges were comprehensively addressed.

Conclusion The solution proposed for the intelligent control of oil pipelines provides a replicable framework for oil and gas pipelines. In the future, with the ongoing evolution of artificial intelligence, enhanced data governance, and the optimization of industrial control systems, the intelligent control technology will keep evolving and be promoted across various oil and gas pipeline networks, ushering in a new era of comprehensive intelligent control.