Abstract: Objective With the global energy structure transitioning and increasing energy demand, the significance of long-distance oil and gas pipelines has become increasingly prominent. Traditional pipeline engineering construction and management models exhibit notable shortcomings when confronted with complex terrains, high construction difficulties, weak safety management, challenging cost control, and intricate multi-party collaboration. There is an urgent need to explore new technological paradigms and management models. Addressing these practical issues, conducting top-level design research on integrated intelligent management and control for long-distance oil and gas pipeline engineering is of substantial practical significance and strategic value. Such efforts aim to promote the industry's digital and intelligent transformation, enhancing the overall efficiency and safety of pipeline construction and operations.​MethodsBased on an analysis of the current status and challenges in domestic and international long-distance oil and gas pipeline engineering construction, this study systematically reviews and summarizes the application status and trends of digital technologies—such as remote sensing, GIS, UAV inspections, big data analytics, artificial intelligence algorithms, and edge computing—in pipeline engineering design, construction, and operations. Utilizing system analysis and framework design methodologies, combined with extensive engineering practices, we construct a top-level design framework for an intelligent management and control system for pipeline engineering.​Results The study proposes four core technological systems: lifecycle data integration and governance, intelligent algorithms and model construction, edge computing and cloud-edge collaboration, and secure and trustworthy assurance. It clarifies the capability system architecture from strategic guidance, organizational collaboration, risk management to value creation. Innovatively, it establishes a lifecycle data closed-loop integration, precise intelligent monitoring, and risk warning mechanism. Additionally, it proposes specific implementation paths and methods for building an intelligent management and control system, demonstrating significant improvements in efficiency and risk control over traditional models.​Conclusion The successful implementation of integrated intelligent management and control for long-distance oil and gas pipeline engineering necessitates the continuous promotion of deep integration between technological innovation and risk management. Future developments should focus on strengthening the construction of standardized systems and data-sharing mechanisms, further overcoming technical barriers and data silos. This study offers direction and practical references for intelligent transformation, aiming to provide theoretical support and practical guidance for the sustainable development of the oil and gas pipeline industry.