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{"title":"二氧化碳含盐含水层封存中两相渗流过程和储层异质性的互为交叉相关分析","authors":"Yiyan Zhong, Qi Li, Liang Xu, Yiping Wen, Yukun Li","doi":"10.1002/ghg.2268","DOIUrl":null,"url":null,"abstract":"<p>When CO<sub>2</sub> saline aquifer storage is carried out, the heterogeneity of reservoir rock is an important factor affecting CO<sub>2</sub> transport, and the reservoir heterogeneity in numerical simulations is mainly manifested as the heterogeneity of the parameter field. Since the parameter distributions across the reservoir are not available with the existing probes, the stochastic finite element method is combined with a two-phase flow model to establish an unconditional random field of permeability, and computations are performed using the Monte Carlo method. The permeability, CO<sub>2</sub> maximum migration distance (<i>M<sub>d</sub></i>) and CO<sub>2</sub> sweep area (<i>S<sub>a</sub></i>) were analyzed for mutual correlation. The permeability correlation area affecting <i>M<sub>d</sub></i> and <i>S<sub>a</sub></i> was obtained, and the changes in the correlation area under the coefficient of variation (<i>C<sub>v</sub></i>) and correlation length (<i>λ<sub>x</sub></i>) of the permeability field in the different reservoirs were analyzed. The kriging superposition approach (KSA) was subsequently used to estimate both the <i>M<sub>d</sub></i> and <i>S<sub>a</sub></i> of the target reservoir by establishing conditional random fields based on the sampling parameters in regions with different correlations, resulting in errors of 0.66% for <i>M<sub>d</sub></i> and 0.96% for <i>S<sub>a</sub></i> in the high correlation region and 4.86% and 3.12% for <i>M<sub>d</sub></i> and <i>S<sub>a</sub></i> in the low correlation region, which suggested that the sampling results from the high correlation region were less biased in the estimation. Under limited sampling conditions, it is recommended that samples be collected in regions with high correlations to reduce the uncertainty of CO<sub>2</sub> transport analysis due to unknown heterogeneity. © 2024 Society of Chemical Industry and John Wiley & Sons, Ltd.</p>","PeriodicalId":12796,"journal":{"name":"Greenhouse Gases: Science and Technology","volume":"14 3","pages":"356-370"},"PeriodicalIF":2.7000,"publicationDate":"2024-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Reciprocal cross-correlation analysis of two-phase seepage processes and reservoir heterogeneities in CO2 saline aquifer sequestration\",\"authors\":\"Yiyan Zhong, Qi Li, Liang Xu, Yiping Wen, Yukun Li\",\"doi\":\"10.1002/ghg.2268\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>When CO<sub>2</sub> saline aquifer storage is carried out, the heterogeneity of reservoir rock is an important factor affecting CO<sub>2</sub> transport, and the reservoir heterogeneity in numerical simulations is mainly manifested as the heterogeneity of the parameter field. Since the parameter distributions across the reservoir are not available with the existing probes, the stochastic finite element method is combined with a two-phase flow model to establish an unconditional random field of permeability, and computations are performed using the Monte Carlo method. The permeability, CO<sub>2</sub> maximum migration distance (<i>M<sub>d</sub></i>) and CO<sub>2</sub> sweep area (<i>S<sub>a</sub></i>) were analyzed for mutual correlation. The permeability correlation area affecting <i>M<sub>d</sub></i> and <i>S<sub>a</sub></i> was obtained, and the changes in the correlation area under the coefficient of variation (<i>C<sub>v</sub></i>) and correlation length (<i>λ<sub>x</sub></i>) of the permeability field in the different reservoirs were analyzed. The kriging superposition approach (KSA) was subsequently used to estimate both the <i>M<sub>d</sub></i> and <i>S<sub>a</sub></i> of the target reservoir by establishing conditional random fields based on the sampling parameters in regions with different correlations, resulting in errors of 0.66% for <i>M<sub>d</sub></i> and 0.96% for <i>S<sub>a</sub></i> in the high correlation region and 4.86% and 3.12% for <i>M<sub>d</sub></i> and <i>S<sub>a</sub></i> in the low correlation region, which suggested that the sampling results from the high correlation region were less biased in the estimation. Under limited sampling conditions, it is recommended that samples be collected in regions with high correlations to reduce the uncertainty of CO<sub>2</sub> transport analysis due to unknown heterogeneity. © 2024 Society of Chemical Industry and John Wiley & Sons, Ltd.</p>\",\"PeriodicalId\":12796,\"journal\":{\"name\":\"Greenhouse Gases: Science and Technology\",\"volume\":\"14 3\",\"pages\":\"356-370\"},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2024-04-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Greenhouse Gases: Science and Technology\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/ghg.2268\",\"RegionNum\":4,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Greenhouse Gases: Science and Technology","FirstCategoryId":"93","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/ghg.2268","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
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