A. Nguyen, Dylan Hematillake, Robert Glover, C. Diaz-Goano
{"title":"Distributed Temperature Sensor Analytics: Estimating SAGD Depletion from Temperature Fall Off Data","authors":"A. Nguyen, Dylan Hematillake, Robert Glover, C. Diaz-Goano","doi":"10.2118/208895-ms","DOIUrl":null,"url":null,"abstract":"\n This paper outlines an end-to-end case study from ideation through to the development and deployment of a novel method to estimate SAGD depletion along a producing SAGD horizontal well from temperature fall off (TFO) events, from any temperature measurement point along the well. The methodology combines reservoir engineering first principals, analytics, simulation modelling and digital product delivery components. The outputs of this work are expected to drive rapid, data-driven, and standardized approaches to subsurface optimization of SAGD well pairs through quantified estimation of remaining oil in place opportunities that could be economically exploited through operations, re-completions, re-drills and technology applications.","PeriodicalId":146458,"journal":{"name":"Day 1 Wed, March 16, 2022","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Day 1 Wed, March 16, 2022","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2118/208895-ms","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
This paper outlines an end-to-end case study from ideation through to the development and deployment of a novel method to estimate SAGD depletion along a producing SAGD horizontal well from temperature fall off (TFO) events, from any temperature measurement point along the well. The methodology combines reservoir engineering first principals, analytics, simulation modelling and digital product delivery components. The outputs of this work are expected to drive rapid, data-driven, and standardized approaches to subsurface optimization of SAGD well pairs through quantified estimation of remaining oil in place opportunities that could be economically exploited through operations, re-completions, re-drills and technology applications.