预出版日期: 2026-05-18
This paper systematically reviews the development stages and status of key oil production engineering domains, including injection-production engineering, artificial lift, reservoir stimulation, and workover operations. On this basis, the major challenges for oil production engineering are identified in four aspects: intelligent endpoint devices and process integration, extreme-environment operations, and collaborative operational constraints; AI-driven data and modeling complexities, and advanced structural and functional material requirements; and the need for geoscience-engineering integration in reservoir characterization, operational efficiency, and green development. Centered on multidisciplinary integration, the concept of the Oil Production Engineering Agent is introduced as a miniaturized, intelligent, integrated hardware-software system designed for extreme downhole environments, incorporating power supply, communication, sensing, computation, and actuation modules to enable environmental perception, autonomous decision-making, and adaptive control. The characteristics of various agent types, including those for injection-production, lift, fracturing, and workover, are analyzed, with key research directions identified in miniaturized self-powered energy management, reliable communication in high-interference environments, highly integrated multi-parameter sensing with long-term drift self-calibration, and high-reliability microsystem integration manufacturing. AI-driven decision optimization remains the core feature, requiring advances in data acquisition, governance, and fusion architectures, alongside algorithmic improvements in model performance and deployment compatibility. Additionally, advanced structural and functional materials support agent construction and extreme-environment adaptability, while geoscience-engineering integration continues to expand the functional scope of oil production engineering.