Jinghong Li , Chuanzhi Cui , Junkang Wang , Yueru Zhang , Guoqiang Li , Youquan Li , Hongbo Li , Fengrui Han
{"title":"利用试井方法确定CO₂-EOR中的CO₂前缘","authors":"Jinghong Li , Chuanzhi Cui , Junkang Wang , Yueru Zhang , Guoqiang Li , Youquan Li , Hongbo Li , Fengrui Han","doi":"10.1016/j.engeos.2025.100385","DOIUrl":null,"url":null,"abstract":"<div><div>CO<sub>2</sub> flooding is a widely recognized method for enhanced oil recovery (EOR). This study aims to develop an accurate prediction method for determining the location and migration pathway of CO<sub>2</sub> front, which plays an essential role in designing effective CO<sub>2</sub> injection schemes and optimizing production strategies. Given the challenges of directly monitoring CO<sub>2</sub> front movement in subsurface reservoirs, numerical well testing serves as an effective tool for indirectly inferring the location and migration characteristics of the CO<sub>2</sub> front. This study established a numerical well-testing model based on a compositional framework to characterize interactions among multiple components during CO<sub>2</sub> flooding. The methodology used in this model involves generating well-testing curves of CO<sub>2</sub> flooding and then determining their flow stages based on CO<sub>2</sub> distribution within reservoirs. Accordingly, a new well-testing analysis approach was proposed to determine the CO<sub>2</sub> zone front and mixing zone front. This approach was applied to a pilot study of a practical oilfield, where it effectively predicted the positions of both fronts. The findings of this study reveal that the CO<sub>2</sub> zone front and the mixing zone front correspond to the beginning of the first horizontal segment and the endpoint of the upward segment in the pressure derivative curve, respectively. This study introduces a cost-effective and time-efficient method for CO₂ front monitoring, addressing the challenges of high costs and prolonged durations typically associated with CO<sub>2</sub>-EOR operations.</div></div>","PeriodicalId":100469,"journal":{"name":"Energy Geoscience","volume":"6 2","pages":"Article 100385"},"PeriodicalIF":3.6000,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Determining CO₂ front in CO₂-EOR using a well-testing method\",\"authors\":\"Jinghong Li , Chuanzhi Cui , Junkang Wang , Yueru Zhang , Guoqiang Li , Youquan Li , Hongbo Li , Fengrui Han\",\"doi\":\"10.1016/j.engeos.2025.100385\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>CO<sub>2</sub> flooding is a widely recognized method for enhanced oil recovery (EOR). This study aims to develop an accurate prediction method for determining the location and migration pathway of CO<sub>2</sub> front, which plays an essential role in designing effective CO<sub>2</sub> injection schemes and optimizing production strategies. Given the challenges of directly monitoring CO<sub>2</sub> front movement in subsurface reservoirs, numerical well testing serves as an effective tool for indirectly inferring the location and migration characteristics of the CO<sub>2</sub> front. This study established a numerical well-testing model based on a compositional framework to characterize interactions among multiple components during CO<sub>2</sub> flooding. The methodology used in this model involves generating well-testing curves of CO<sub>2</sub> flooding and then determining their flow stages based on CO<sub>2</sub> distribution within reservoirs. Accordingly, a new well-testing analysis approach was proposed to determine the CO<sub>2</sub> zone front and mixing zone front. This approach was applied to a pilot study of a practical oilfield, where it effectively predicted the positions of both fronts. The findings of this study reveal that the CO<sub>2</sub> zone front and the mixing zone front correspond to the beginning of the first horizontal segment and the endpoint of the upward segment in the pressure derivative curve, respectively. This study introduces a cost-effective and time-efficient method for CO₂ front monitoring, addressing the challenges of high costs and prolonged durations typically associated with CO<sub>2</sub>-EOR operations.</div></div>\",\"PeriodicalId\":100469,\"journal\":{\"name\":\"Energy Geoscience\",\"volume\":\"6 2\",\"pages\":\"Article 100385\"},\"PeriodicalIF\":3.6000,\"publicationDate\":\"2025-02-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Energy Geoscience\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S266675922500006X\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy Geoscience","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S266675922500006X","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Determining CO₂ front in CO₂-EOR using a well-testing method
CO2 flooding is a widely recognized method for enhanced oil recovery (EOR). This study aims to develop an accurate prediction method for determining the location and migration pathway of CO2 front, which plays an essential role in designing effective CO2 injection schemes and optimizing production strategies. Given the challenges of directly monitoring CO2 front movement in subsurface reservoirs, numerical well testing serves as an effective tool for indirectly inferring the location and migration characteristics of the CO2 front. This study established a numerical well-testing model based on a compositional framework to characterize interactions among multiple components during CO2 flooding. The methodology used in this model involves generating well-testing curves of CO2 flooding and then determining their flow stages based on CO2 distribution within reservoirs. Accordingly, a new well-testing analysis approach was proposed to determine the CO2 zone front and mixing zone front. This approach was applied to a pilot study of a practical oilfield, where it effectively predicted the positions of both fronts. The findings of this study reveal that the CO2 zone front and the mixing zone front correspond to the beginning of the first horizontal segment and the endpoint of the upward segment in the pressure derivative curve, respectively. This study introduces a cost-effective and time-efficient method for CO₂ front monitoring, addressing the challenges of high costs and prolonged durations typically associated with CO2-EOR operations.