R. Rommetveit, M. G. Mayani, J. Nabavi, Stig Helgeland, Raymond Hammer, Jostein Råen
{"title":"利用数字孪生技术自动实时监测钻井,提高了安全性,降低了成本","authors":"R. Rommetveit, M. G. Mayani, J. Nabavi, Stig Helgeland, Raymond Hammer, Jostein Råen","doi":"10.2118/197465-ms","DOIUrl":null,"url":null,"abstract":"\n As part of the digital transformation in oil and gas industry, well construction move toward new efficient methods using digital twins of the wells. This paper will highlight how the drilling operations are monitored, how a digital twin of the well is utilized and how learnings are implemented for future wells.\n A Digital Twin is a digital copy of assets, systems and processes. A Digital Twin in drilling is an exact digital replica of the physical well during the whole drilling life cycle. Its functionality is based on advanced hydraulic and dynamic models processing in real time. By utilizing real-time data from the well, it enables automatic analysis of data and monitoring of the drilling operation and offer early diagnostic messages to detect early signs of problems or incidents.\n In the current study various actual operational cases will be presented related to different wells. This includes using digital twin during drilling under challenging circumstances such as conditions when using MPD techniques. Also, various diagnostic messages which gave early signs of problems during running in the hole, pulling out of the hole and drilling will be presented. High restrictions were detected using comparisons of real-time values and transient modelling results. These will be discussed.\n Different real cases have been studied. Combining digital RT modelled and real-time measured data in combination with predictive diagnostic messages will improve the decision making and result in less non-productive time and more optimal drilling operations.","PeriodicalId":11328,"journal":{"name":"Day 4 Thu, November 14, 2019","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Automatic Realtime Monitoring of Drilling Using Digital Twin Technologies Enhance Safety and Reduce Costs\",\"authors\":\"R. Rommetveit, M. G. Mayani, J. Nabavi, Stig Helgeland, Raymond Hammer, Jostein Råen\",\"doi\":\"10.2118/197465-ms\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n As part of the digital transformation in oil and gas industry, well construction move toward new efficient methods using digital twins of the wells. This paper will highlight how the drilling operations are monitored, how a digital twin of the well is utilized and how learnings are implemented for future wells.\\n A Digital Twin is a digital copy of assets, systems and processes. A Digital Twin in drilling is an exact digital replica of the physical well during the whole drilling life cycle. Its functionality is based on advanced hydraulic and dynamic models processing in real time. By utilizing real-time data from the well, it enables automatic analysis of data and monitoring of the drilling operation and offer early diagnostic messages to detect early signs of problems or incidents.\\n In the current study various actual operational cases will be presented related to different wells. This includes using digital twin during drilling under challenging circumstances such as conditions when using MPD techniques. Also, various diagnostic messages which gave early signs of problems during running in the hole, pulling out of the hole and drilling will be presented. High restrictions were detected using comparisons of real-time values and transient modelling results. These will be discussed.\\n Different real cases have been studied. Combining digital RT modelled and real-time measured data in combination with predictive diagnostic messages will improve the decision making and result in less non-productive time and more optimal drilling operations.\",\"PeriodicalId\":11328,\"journal\":{\"name\":\"Day 4 Thu, November 14, 2019\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Day 4 Thu, November 14, 2019\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2118/197465-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 4 Thu, November 14, 2019","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2118/197465-ms","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Automatic Realtime Monitoring of Drilling Using Digital Twin Technologies Enhance Safety and Reduce Costs
As part of the digital transformation in oil and gas industry, well construction move toward new efficient methods using digital twins of the wells. This paper will highlight how the drilling operations are monitored, how a digital twin of the well is utilized and how learnings are implemented for future wells.
A Digital Twin is a digital copy of assets, systems and processes. A Digital Twin in drilling is an exact digital replica of the physical well during the whole drilling life cycle. Its functionality is based on advanced hydraulic and dynamic models processing in real time. By utilizing real-time data from the well, it enables automatic analysis of data and monitoring of the drilling operation and offer early diagnostic messages to detect early signs of problems or incidents.
In the current study various actual operational cases will be presented related to different wells. This includes using digital twin during drilling under challenging circumstances such as conditions when using MPD techniques. Also, various diagnostic messages which gave early signs of problems during running in the hole, pulling out of the hole and drilling will be presented. High restrictions were detected using comparisons of real-time values and transient modelling results. These will be discussed.
Different real cases have been studied. Combining digital RT modelled and real-time measured data in combination with predictive diagnostic messages will improve the decision making and result in less non-productive time and more optimal drilling operations.