{"title":"利用路径、源云和时间云监测和可视化CO2羽流","authors":"Hongquan Chen, Ao Li","doi":"10.1016/j.geoen.2025.214093","DOIUrl":null,"url":null,"abstract":"<div><div>Effective monitoring of subsurface fluid motion is crucial for successful carbon sequestration. While streamlines are commonly used to visualize fluid flow, they are based on instantaneous velocity fields and do not account for changing field conditions. To address this problem, pathlines are introduced to track the history of individual fluid particles as they move in a changing velocity field.</div><div>This paper presents the development and application of pathlines for flow visualization in CO<sub>2</sub> storage projects. By splicing streamline segments over time, pathlines can trace the trajectory of a particle under a changing velocity field. In addition, streaklines and timelines can be visualized from pathlines. Streaklines represent all fluid particles emitted at the same location, while timelines show the contour formed by all fluid particles emitted at the same instant, representing the fluid front movement. In 3D, these concepts are visualized in groups of points, referred to as source cloud and time cloud.</div><div>To test the effectiveness of our proposed injection monitoring methods, we conducted experiments on 3D synthetic CO<sub>2</sub> storage models. The results show that pathlines, source cloud and time cloud provide a more accurate display of the CO<sub>2</sub> plume than streamlines, particularly in field situations where well schedules are changing.</div><div>Finally, we applied the proposed method to visualize the CO<sub>2</sub> plume in a sequestration model based on Norway's Sleipner site. Under dynamic injection, the pathline-based swept volume closely matched the CO<sub>2</sub> saturation-defined volume (95 % overlap), while the streamline-based volume overestimated it by 127 %. This highlights the effectiveness of pathlines, source cloud, and time cloud for CCUS visualization.</div></div>","PeriodicalId":100578,"journal":{"name":"Geoenergy Science and Engineering","volume":"255 ","pages":"Article 214093"},"PeriodicalIF":4.6000,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"CO2 plume monitoring and visualization using pathlines, source cloud and time cloud\",\"authors\":\"Hongquan Chen, Ao Li\",\"doi\":\"10.1016/j.geoen.2025.214093\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Effective monitoring of subsurface fluid motion is crucial for successful carbon sequestration. While streamlines are commonly used to visualize fluid flow, they are based on instantaneous velocity fields and do not account for changing field conditions. To address this problem, pathlines are introduced to track the history of individual fluid particles as they move in a changing velocity field.</div><div>This paper presents the development and application of pathlines for flow visualization in CO<sub>2</sub> storage projects. By splicing streamline segments over time, pathlines can trace the trajectory of a particle under a changing velocity field. In addition, streaklines and timelines can be visualized from pathlines. Streaklines represent all fluid particles emitted at the same location, while timelines show the contour formed by all fluid particles emitted at the same instant, representing the fluid front movement. In 3D, these concepts are visualized in groups of points, referred to as source cloud and time cloud.</div><div>To test the effectiveness of our proposed injection monitoring methods, we conducted experiments on 3D synthetic CO<sub>2</sub> storage models. The results show that pathlines, source cloud and time cloud provide a more accurate display of the CO<sub>2</sub> plume than streamlines, particularly in field situations where well schedules are changing.</div><div>Finally, we applied the proposed method to visualize the CO<sub>2</sub> plume in a sequestration model based on Norway's Sleipner site. Under dynamic injection, the pathline-based swept volume closely matched the CO<sub>2</sub> saturation-defined volume (95 % overlap), while the streamline-based volume overestimated it by 127 %. This highlights the effectiveness of pathlines, source cloud, and time cloud for CCUS visualization.</div></div>\",\"PeriodicalId\":100578,\"journal\":{\"name\":\"Geoenergy Science and Engineering\",\"volume\":\"255 \",\"pages\":\"Article 214093\"},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2025-07-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Geoenergy Science and Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2949891025004518\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"0\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geoenergy Science and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2949891025004518","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"0","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
CO2 plume monitoring and visualization using pathlines, source cloud and time cloud
Effective monitoring of subsurface fluid motion is crucial for successful carbon sequestration. While streamlines are commonly used to visualize fluid flow, they are based on instantaneous velocity fields and do not account for changing field conditions. To address this problem, pathlines are introduced to track the history of individual fluid particles as they move in a changing velocity field.
This paper presents the development and application of pathlines for flow visualization in CO2 storage projects. By splicing streamline segments over time, pathlines can trace the trajectory of a particle under a changing velocity field. In addition, streaklines and timelines can be visualized from pathlines. Streaklines represent all fluid particles emitted at the same location, while timelines show the contour formed by all fluid particles emitted at the same instant, representing the fluid front movement. In 3D, these concepts are visualized in groups of points, referred to as source cloud and time cloud.
To test the effectiveness of our proposed injection monitoring methods, we conducted experiments on 3D synthetic CO2 storage models. The results show that pathlines, source cloud and time cloud provide a more accurate display of the CO2 plume than streamlines, particularly in field situations where well schedules are changing.
Finally, we applied the proposed method to visualize the CO2 plume in a sequestration model based on Norway's Sleipner site. Under dynamic injection, the pathline-based swept volume closely matched the CO2 saturation-defined volume (95 % overlap), while the streamline-based volume overestimated it by 127 %. This highlights the effectiveness of pathlines, source cloud, and time cloud for CCUS visualization.