Objective The PipeChina Oil & Gas Control Center has independently developed an application platform for the operational data of its natural gas pipeline network, in an attempt to fully explore the value of network operational data and to address issues such as low data value density, significant heterogeneity of data sources, incomplete data acquisition and aggregation, insufficient data circulation and sharing, a lack of in-depth development and application, and notable weaknesses in data governance and security.
Methods The underlying data structure of this platform was constructed using a relational database, fully leveraging the automated data acquisition process and remote control technology of key equipment. This structure enables a panoramic perception of the network's operational dynamics. Further research and development efforts led to the creation of data exchange technology with unified lower features, aimed at exploring the value of operational data within its network, optimizing the data structure, and integrating data assets. Additionally, the display interfaces for production and operational data were optimized, significantly reducing the workload associated with data queries and enabling operation management and analysis personnel to quickly access real-time production information, operational status, and historical data for these pipelines. Furthermore, deep learning algorithms and feature enhancement technologies were introduced to support the prediction of key gas volume parameters in the natural gas pipeline network.
Results The application platform established for operational data of the natural gas pipeline network facilitates the interactive sharing of various data types, including SCADA data, intermediate pipeline data, production and operational management data, ledgers, statements, and simulation optimization data. It also supports the creation of a physical parameter database for the pipeline network system. This setup enables the standardized application of multi-source and multi-scale high-dimensional data sharing, thereby enhancing data utilization levels.
Conclusion The efficient utilization of the application platform for operational data of the natural gas pipeline network could significantly enhance data application levels at the PipeChina Oil & Gas Control Center. This improvement would strengthen the capabilities of pipeline network control and supply assurance during emergencies and support PipeChina's digital transformation toward the vision of "smart pipeline network, intelligent pipelines, and intelligent control".
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