L. Zhen, Lin Guanjun, Li Shusheng, Wang Weibin, L. Xiaoming
{"title":"Research on the future development scheme of the oil big data industry","authors":"L. Zhen, Lin Guanjun, Li Shusheng, Wang Weibin, L. Xiaoming","doi":"10.1109/ITME53901.2021.00019","DOIUrl":null,"url":null,"abstract":"At present, the big data industry is developing rapidly in many fields around the world, and it brings opportunities for the transformation and upgradation of the traditional oil industry. The whole oil business chain is of large scale, and there are urgent needs to apply big data technologies in the fields of petroleum exploration and development, transportation, refining and other fields. However, the oil big data industry is still in its infancy and has encountered many challenges, including oil data storage and management being not standardized, technical standards being not unified, and security concerns. These issues further lead to the poor data sharing, repeated business deployment within the enterprise and the compromised of the systems. To solve the problems above, this paper proposes the overall architecture for the development of the oil big data industry. The architecture scheme integrates all the data and business of the oil industry chain, which allows the secure data sharing, effective business management and scientific allocation of resources. Therefore, the oil big data solution can provide an important research idea for the dynamic management of production process and industrial business, which improves the overall productivity of oil industry.","PeriodicalId":6774,"journal":{"name":"2021 11th International Conference on Information Technology in Medicine and Education (ITME)","volume":"13 1","pages":"42-46"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 11th International Conference on Information Technology in Medicine and Education (ITME)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITME53901.2021.00019","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
At present, the big data industry is developing rapidly in many fields around the world, and it brings opportunities for the transformation and upgradation of the traditional oil industry. The whole oil business chain is of large scale, and there are urgent needs to apply big data technologies in the fields of petroleum exploration and development, transportation, refining and other fields. However, the oil big data industry is still in its infancy and has encountered many challenges, including oil data storage and management being not standardized, technical standards being not unified, and security concerns. These issues further lead to the poor data sharing, repeated business deployment within the enterprise and the compromised of the systems. To solve the problems above, this paper proposes the overall architecture for the development of the oil big data industry. The architecture scheme integrates all the data and business of the oil industry chain, which allows the secure data sharing, effective business management and scientific allocation of resources. Therefore, the oil big data solution can provide an important research idea for the dynamic management of production process and industrial business, which improves the overall productivity of oil industry.