ShiJie Li, HuiYuan Bian, Di Zhang, YanXin Liu, GuoLiang Liu, Fei Wang
{"title":"基于分形理论的致密油藏孔隙结构与分类评价研究","authors":"ShiJie Li, HuiYuan Bian, Di Zhang, YanXin Liu, GuoLiang Liu, Fei Wang","doi":"10.1007/s11600-024-01299-2","DOIUrl":null,"url":null,"abstract":"<div><p>The Chang 8 formation of the Yanchang Group, located in Yuancheng area of the Ordos Basin, is a typical tight oil reservoir in China. This reservoir is characterized by low porosity, low permeability, strong non-homogeneity, and significant difficulty in evaluating the reservoir parameters. To examine and investigate the microscopic pore structure characteristics of the Chang 8 formation, cast thin section and scanning electron microscopy techniques were utilized in this study, Moreover, tests on the core physical properties were conducted and the data from these tests were integrated into the analysis of basic characteristics of the reservoir rock mineralogy, pore permeability, and other fundamental characteristics. The shapes of piezomercury curves were systematically examined to study the characteristics and features of pore structures for the 17 samples. In accordance with the fractal dimension of the NMR <i>T</i><sub>2</sub> spectrum, the reservoir was classified into four categories, and a conversion model delineating the correlation between the NMR <i>T</i><sub>2</sub> spectrum and the capillary pressure curve was formulated through the application of the segmented power function method. This model was then implemented in the interpretation of NMR logging, facilitating the acquisition of a seamless pseudo-capillary pressure curve spanning the entire well section. Three essential parameters reflecting the microscopic pore structure, namely the expulsion pressure, median pressure, and sorting coefficient of the core samples, were extracted. The association between reservoir parameters and reservoir categorization was then determined through the application of a generalized regression neural network. The pseudo-capillary pressure curve reservoir parameters of the whole well section were processed to derive the classification profile of the reservoir, and the classification results demonstrated a strong alignment with those of the mercury injection experiments. This study highlights that the proposed method can provide crucial foundation for the investigations on pore structures in tight oil reservoirs and the evaluation of reservoir classification.</p></div>","PeriodicalId":6988,"journal":{"name":"Acta Geophysica","volume":"72 6","pages":"4079 - 4089"},"PeriodicalIF":2.3000,"publicationDate":"2024-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s11600-024-01299-2.pdf","citationCount":"0","resultStr":"{\"title\":\"Research on pore structure and classification evaluation of tight oil reservoirs based on fractal theory\",\"authors\":\"ShiJie Li, HuiYuan Bian, Di Zhang, YanXin Liu, GuoLiang Liu, Fei Wang\",\"doi\":\"10.1007/s11600-024-01299-2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The Chang 8 formation of the Yanchang Group, located in Yuancheng area of the Ordos Basin, is a typical tight oil reservoir in China. This reservoir is characterized by low porosity, low permeability, strong non-homogeneity, and significant difficulty in evaluating the reservoir parameters. To examine and investigate the microscopic pore structure characteristics of the Chang 8 formation, cast thin section and scanning electron microscopy techniques were utilized in this study, Moreover, tests on the core physical properties were conducted and the data from these tests were integrated into the analysis of basic characteristics of the reservoir rock mineralogy, pore permeability, and other fundamental characteristics. The shapes of piezomercury curves were systematically examined to study the characteristics and features of pore structures for the 17 samples. In accordance with the fractal dimension of the NMR <i>T</i><sub>2</sub> spectrum, the reservoir was classified into four categories, and a conversion model delineating the correlation between the NMR <i>T</i><sub>2</sub> spectrum and the capillary pressure curve was formulated through the application of the segmented power function method. This model was then implemented in the interpretation of NMR logging, facilitating the acquisition of a seamless pseudo-capillary pressure curve spanning the entire well section. Three essential parameters reflecting the microscopic pore structure, namely the expulsion pressure, median pressure, and sorting coefficient of the core samples, were extracted. The association between reservoir parameters and reservoir categorization was then determined through the application of a generalized regression neural network. The pseudo-capillary pressure curve reservoir parameters of the whole well section were processed to derive the classification profile of the reservoir, and the classification results demonstrated a strong alignment with those of the mercury injection experiments. This study highlights that the proposed method can provide crucial foundation for the investigations on pore structures in tight oil reservoirs and the evaluation of reservoir classification.</p></div>\",\"PeriodicalId\":6988,\"journal\":{\"name\":\"Acta Geophysica\",\"volume\":\"72 6\",\"pages\":\"4079 - 4089\"},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2024-03-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://link.springer.com/content/pdf/10.1007/s11600-024-01299-2.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Acta Geophysica\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s11600-024-01299-2\",\"RegionNum\":4,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Acta Geophysica","FirstCategoryId":"89","ListUrlMain":"https://link.springer.com/article/10.1007/s11600-024-01299-2","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on pore structure and classification evaluation of tight oil reservoirs based on fractal theory
The Chang 8 formation of the Yanchang Group, located in Yuancheng area of the Ordos Basin, is a typical tight oil reservoir in China. This reservoir is characterized by low porosity, low permeability, strong non-homogeneity, and significant difficulty in evaluating the reservoir parameters. To examine and investigate the microscopic pore structure characteristics of the Chang 8 formation, cast thin section and scanning electron microscopy techniques were utilized in this study, Moreover, tests on the core physical properties were conducted and the data from these tests were integrated into the analysis of basic characteristics of the reservoir rock mineralogy, pore permeability, and other fundamental characteristics. The shapes of piezomercury curves were systematically examined to study the characteristics and features of pore structures for the 17 samples. In accordance with the fractal dimension of the NMR T2 spectrum, the reservoir was classified into four categories, and a conversion model delineating the correlation between the NMR T2 spectrum and the capillary pressure curve was formulated through the application of the segmented power function method. This model was then implemented in the interpretation of NMR logging, facilitating the acquisition of a seamless pseudo-capillary pressure curve spanning the entire well section. Three essential parameters reflecting the microscopic pore structure, namely the expulsion pressure, median pressure, and sorting coefficient of the core samples, were extracted. The association between reservoir parameters and reservoir categorization was then determined through the application of a generalized regression neural network. The pseudo-capillary pressure curve reservoir parameters of the whole well section were processed to derive the classification profile of the reservoir, and the classification results demonstrated a strong alignment with those of the mercury injection experiments. This study highlights that the proposed method can provide crucial foundation for the investigations on pore structures in tight oil reservoirs and the evaluation of reservoir classification.
期刊介绍:
Acta Geophysica is open to all kinds of manuscripts including research and review articles, short communications, comments to published papers, letters to the Editor as well as book reviews. Some of the issues are fully devoted to particular topics; we do encourage proposals for such topical issues. We accept submissions from scientists world-wide, offering high scientific and editorial standard and comprehensive treatment of the discussed topics.