C. Sanasi, Luca Dal Forno, Giorgio Ricci Maccarini, Luigi Mutidieri, P. Tempone, D. Mezzapesa, Matilde Dalla Rosa, Alessandro Bucci, F. Rinaldi, C. Andreoletti
{"title":"支持业务发展的公司数据治理转型","authors":"C. Sanasi, Luca Dal Forno, Giorgio Ricci Maccarini, Luigi Mutidieri, P. Tempone, D. Mezzapesa, Matilde Dalla Rosa, Alessandro Bucci, F. Rinaldi, C. Andreoletti","doi":"10.2118/207525-ms","DOIUrl":null,"url":null,"abstract":"\n The evolution of the energy market requires companies to increase their operating efficiency, leveraging on collaborative environment and existing assets, including Data. A new focus on data governance and integration is needed to maximize the value of data and ensure \"real-time\" efficient response.\n The decoupling of data from applications enables organization by domain and data type in one cross-functional data hub. This scheme is independent from the scope of the activity and will therefore maintain its validity when dealing with new business requiring subsurface data utilization. The integrated data platform will feed advanced digital tools capable to control the risks, optimize performance and reduce emissions associated with the operations.\n Eni is putting this idea into practice with a new data infrastructure which is integrated across all the subsurface disciplines (G&G, Exploration, Upstream Laboratories, Reservoir and Well Operations departments). In this paper, the example of real time data exploitation will be discussed.\n Real time data workflow was first established in well operations for operational supervision and later developed for real time performance optimization, through the introduction of predictive analytics. Its latest evolution in the broader subsurface domain encompasses the application of AI to operations geology processes and the extension to all operated activities. This approach will equally support new company goals, such as decarbonization, increasing performance of subsurface activities related to underground storage of CO2 in depleted reservoirs.","PeriodicalId":11069,"journal":{"name":"Day 2 Tue, November 16, 2021","volume":"17 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Company Data Governance Transformation to Support the Business Evolution\",\"authors\":\"C. Sanasi, Luca Dal Forno, Giorgio Ricci Maccarini, Luigi Mutidieri, P. Tempone, D. Mezzapesa, Matilde Dalla Rosa, Alessandro Bucci, F. Rinaldi, C. Andreoletti\",\"doi\":\"10.2118/207525-ms\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n The evolution of the energy market requires companies to increase their operating efficiency, leveraging on collaborative environment and existing assets, including Data. A new focus on data governance and integration is needed to maximize the value of data and ensure \\\"real-time\\\" efficient response.\\n The decoupling of data from applications enables organization by domain and data type in one cross-functional data hub. This scheme is independent from the scope of the activity and will therefore maintain its validity when dealing with new business requiring subsurface data utilization. The integrated data platform will feed advanced digital tools capable to control the risks, optimize performance and reduce emissions associated with the operations.\\n Eni is putting this idea into practice with a new data infrastructure which is integrated across all the subsurface disciplines (G&G, Exploration, Upstream Laboratories, Reservoir and Well Operations departments). In this paper, the example of real time data exploitation will be discussed.\\n Real time data workflow was first established in well operations for operational supervision and later developed for real time performance optimization, through the introduction of predictive analytics. Its latest evolution in the broader subsurface domain encompasses the application of AI to operations geology processes and the extension to all operated activities. This approach will equally support new company goals, such as decarbonization, increasing performance of subsurface activities related to underground storage of CO2 in depleted reservoirs.\",\"PeriodicalId\":11069,\"journal\":{\"name\":\"Day 2 Tue, November 16, 2021\",\"volume\":\"17 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Day 2 Tue, November 16, 2021\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2118/207525-ms\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Day 2 Tue, November 16, 2021","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2118/207525-ms","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Company Data Governance Transformation to Support the Business Evolution
The evolution of the energy market requires companies to increase their operating efficiency, leveraging on collaborative environment and existing assets, including Data. A new focus on data governance and integration is needed to maximize the value of data and ensure "real-time" efficient response.
The decoupling of data from applications enables organization by domain and data type in one cross-functional data hub. This scheme is independent from the scope of the activity and will therefore maintain its validity when dealing with new business requiring subsurface data utilization. The integrated data platform will feed advanced digital tools capable to control the risks, optimize performance and reduce emissions associated with the operations.
Eni is putting this idea into practice with a new data infrastructure which is integrated across all the subsurface disciplines (G&G, Exploration, Upstream Laboratories, Reservoir and Well Operations departments). In this paper, the example of real time data exploitation will be discussed.
Real time data workflow was first established in well operations for operational supervision and later developed for real time performance optimization, through the introduction of predictive analytics. Its latest evolution in the broader subsurface domain encompasses the application of AI to operations geology processes and the extension to all operated activities. This approach will equally support new company goals, such as decarbonization, increasing performance of subsurface activities related to underground storage of CO2 in depleted reservoirs.