混合建模方法在油气管网中的应用初探

Preliminary study on application of hybrid modeling method in oil and gas pipeline networks

大型油气管网具有源汇节点多、空间跨度大、热力水力过程耦合程度高等特点,导致建模难度大。国家《中长期油气管网规划》指出,管网智能化是未来方向,融合机理知识与数据驱动建模方法,构建物理意义明确、外推泛化能力强的混合模型是实现智慧管网的关键环节。分析机理建模与数据驱动建模方法的特点,通过融合机理模型与数据驱动模型协同描述研究对象的物理特性,充分挖掘现场数据内在关联,探索过程变量演化规律,最终建成了机理-数据双驱动的高保真混合模型。梳理混合建模不同结构及其在油气管道行业应用的可行性,阐明了不同应用场景下混合建模的策略,探讨了机理与数据驱动协同建模技术的研究方向,以期为智慧管网建设提供参考。(图2,参60)

Large oil and gas pipeline networks are characterized by multiple source and sink nodes,large spatial span and high degree of coupling between the thermal and hydraulic processes,which lead to great difficulty in modeling.It is pointed out in the Medium and long-term oil and gas pipeline network planning that the intellectualization of pipeline networks is the development direction in the future,and building a hybrid model with clear physical meaning and strong generalization capabilities by combining the mechanism knowledge and the data-driven modeling method is critical to realize the intelligent pipeline networks.Herein,the characteristics of mechanism modeling and data-driven modeling were analyzed,the physical properties of the study object were described collaboratively by integrating the mechanism model and the datadriven model,the internal connection among the site data was fully mined,the evolution laws of the process variations were explored,and finally a high-fidelity hybrid model was established.In addition,various structures of hybrid models and the feasibility of their application in oil and gas pipeline industry was summarized,the strategies of hybrid modeling in various application scenarios were clarified and the direction of research on the mechanism and data based collaborative modeling technology in future was discussed.Further,the research results can provide reference to the construction of intelligent pipeline networks.(2 Figures,60 References)