| China’s dependence on foreign oil consumption has always been high.By 2021,China’s dependence on foreign oil has exceeded 70% for three consecutive years.With the further development of high-quality economy,accelerated urbanization and further improvement of industrial capacity,this phenomenon is likely to become more serious.Since the vast majority of our oil imports are transported by sea,once the sea transport channel is blocked due to weather and other reasons,it may affect our oil endconsumption users,and even affect the economy and employment.Real-time tracking of offshore oil transport and quantitative calculation of possible impacts can effectively grasp the expected effects of impacts and take countermeasures.Although many strategic scientists have carried out a large number of statistical analysis of resource security situation,most of them are based on traditional "tabular" visual analysis,which has shortcomings such as delayed data update,difficulty in processing complex data and low efficiency.At present,the economic game situation between China and the United States is increasingly severe,and rapid analysis is imperative to adapt to the era of big data,which is of great strategic significance to national security.Based on the theories and technologies of big data,GIS and artificial intelligence,this paper studies China’s oil consumption,overseas supply,security and other issues,solves a series of key technical problems and makes the following achievements and progress:(1)The event-driven intelligent analysis mode of oil security is proposed: when emergent major events such as war,public health,weather,piracy,disaster,etc.,one or more links in the whole oil industry chain can be intelligently analyzed and mined from multiple angles,and a new "event-computation-response-countermeasures" working mode oriented to oil security can be realized.(2)Put forward a new oil safety deduction model for the whole industry chain:when China’s oil imports at sea are confronted with safety incidents,a process and systematic deduction model is developed for oil output from oil exporting countries and ports to terminals of oil input ports,refineries and gas stations in China.The design covers production,transportation,processing,consumption and other major categories of influencing factors,providing a blueprint for multi-level analysis and mining of petroleum security.(3)Build an intelligent analysis platform for oil security: Based on big data,GIS,artificial intelligence,cloud computing,Internet of Things and other technical means,build a framework of oil security system driven by spatiotemporal big data for automatic calculation,reflecting the whole process of collection,management,analysis,sharing,analysis mining and application of multi-source spatiotemporal big data.(4)Design the spatiotemporal big data fusion model for oil security:comprehensively analyze the demand for oil security inference,and adopt the big data technology and methods to design the data fusion model with spatiotemporal characteristics involving oil tankers,oil-producing countries,export ports,import ports,importing countries,etc.,to provide data support for the intelligent inference of oil supply.(5)Developed an enterprise-level intelligent inference system for oil security:Based on object-oriented analysis and design,the petroleum security software system is implemented by using advanced software technologies such as MVVM,Arc GIS Runtime,and C# programming language.In the whole event-based process,various information visualization methods such as automatic operation,picture-table-document-video and map are adopted.Vividly show the whole process of dynamic deduction link.The system has been deployed and operated in the Global Strategy Research Center of Chinese Academy of Geological Sciences,and has been recognized by users and experts. |
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