Objective Against the backdrop of profound global energy restructuring and the pursuit of “dual-carbon” goals, oil and gas pipelines play a critical role in connecting energy production and consumption. Consequently, their efficient transmission and safety are vital to the stability of energy systems. However, traditional engineering construction and operational models struggle to meet the complex management requirements and technical challenges that have emerged. To address these issues, this paper explores the implementation pathway for integrated intelligent management and control in oil and gas pipeline engineering, with a particular focus on resolving data quality issues. The aim is to provide theoretical support and technical guidance for the intelligent upgrading of the oil and gas industry.

Methods By revealing the development patterns of data applications based on the characteristics in the three stages of the construction toward intelligence in oil and gas pipeline engineering, this initial investigation identified data quality as the core bottleneck hindering progress toward intelligence and analyzed the specific challenges associated with data applications. Following this, a six-level overall architecture for integrated intelligent management and control was established, encompassing the equipment and facility layer, edge layer, resource layer, platform layer, application layer, and presentation layer. Subsequently, a detailed analysis was conducted to examine functional correlations with pipeline operation at these levels of integrated intelligent management and control during pipeline construction. Consequently, with a focus on the primary goal of improving data quality, solutions and implementation pathways were proposed for the application of the proposed overall architecture, considering the aspects of data collection, data processing, data application, and data transfer. Furthermore, this overall architecture was applied practically in typical scenarios.

Results Through the application of the proposed overall architecture for integrated intelligent management and control, an engineering model incorporating both digital and intelligent capabilities was developed to facilitate a seamless transition from the construction period to the operation period. This model provides an effective approach to address inadequacies in data integrity, consistency, accuracy, and availability, significantly enhancing support for intelligent decision-making. A case study based on an LNG terminal and the supporting export pipeline of Fujian Kunlun Energy Liquefied Natural Gas Co., Ltd., CNPC, validated the effectiveness of the proposed architecture in several areas, including improving data quality, reducing business process time, and lowering project investment costs, underscoring significantly elevated levels of intelligence in typical scenarios.

Conclusion The systematic solutions developed in this research provide a replicable integrated intelligent management and control paradigm for oil and gas pipeline engineering, offering significant reference value for the industry’s intelligent upgrade. With the deep integration of modern information technologies such as big data and artificial intelligence, along with the gradual refinement into a unified standard framework in the future, the oil and gas pipeline industry is poised for further development in intelligence, both in depth and breadth. Continuously optimizing data governance capabilities and strengthening technological integration and innovation are recognized as essential for advancing the industry to a higher level of intelligence.