{"title":"柴达木盆地西南颖西地区硅屑-碳酸盐岩混合孔隙结构及分形特征","authors":"Xinlei Zhang, Zhiqian Gao, V. Maselli, T. Fan","doi":"10.2118/215839-pa","DOIUrl":null,"url":null,"abstract":"\n Evaluating reservoir properties at the pore scale is vital to better estimate hydrocarbon reserves and plan field development. The lacustrine mixed siliciclastic-carbonate deposits of the Upper Paleogene Xiaganchaigou Formation in the west Yingxiongling area form one of the most important hydrocarbon reservoirs in the southwestern Qaidam Basin (China). In this study, we analyzed well samples with X-ray diffraction (XRD), nuclear magnetic resonance (NMR), and mercury injection capillary pressure (MICP) data in integration with scanning electron microscopy (SEM) images to decipher the mineral composition and pore structure characteristics of the Xiaganchaigou Formation. We also calculate the fractal dimensions using MICP, NMR T2 spectrum, and SEM images based on fractal theory models. The results indicate that the mixed siliciclastic-carbonate samples of the upper section of the Xiaganchaigou Formation are mainly formed by dolomite and clay minerals with low siliceous and calcite content. Porosity is relatively low (2.01−9.83%) and positively correlated with dolomite content, thus indicating that the dolomite intercrystalline pores formed by infiltration and reflux dolomitization control the reservoir characteristics. The size of dolomite intercrystalline pores varies between several and hundreds of nanometers. The porosity has a poor correlation with permeability, which indicates that the pores are mostly primary, which lack the transformation of late dissolution. Three types of mixed siliciclastic-carbonate reservoirs are identified according to pore size distribution (<20 nm, 20−300 nm and multiple distribution), calculated using the NMR T2 spectrum. Fractal curves calculated by combining the MICP and NMR data are characterized by multisegments. The number of segments depends on the degree of heterogeneity of pore structure: two segment for high heterogeneity and three segment for low heterogeneity, also indicating a multifractal feature in mixed rock reservoirs. There is a negative correlation trend between porosity and fractal dimensions, and larger pores often have larger fractal dimensions. These results show that MICP-based fractal values are higher than those of NMR-based, which result from unconnected pores that the MICP is unable to reach. Fractal dimensions obtained from SEM have a small and narrow distribution range and are negatively correlated with the number of pores with smaller sizes. In essence, this study shows that the fractal dimension can be a concise index to evaluate the heterogeneity of lacustrine mixed siliciclastic-carbonate reservoirs, which can serve as an important reference for hydrocarbon development plans.","PeriodicalId":22066,"journal":{"name":"SPE Reservoir Evaluation & Engineering","volume":"78 1","pages":""},"PeriodicalIF":2.1000,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Pore Structure and Fractal Characteristics of Mixed Siliciclastic-Carbonate Rocks from the Yingxi Area, Southwest Qaidam Basin, China\",\"authors\":\"Xinlei Zhang, Zhiqian Gao, V. Maselli, T. Fan\",\"doi\":\"10.2118/215839-pa\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n Evaluating reservoir properties at the pore scale is vital to better estimate hydrocarbon reserves and plan field development. The lacustrine mixed siliciclastic-carbonate deposits of the Upper Paleogene Xiaganchaigou Formation in the west Yingxiongling area form one of the most important hydrocarbon reservoirs in the southwestern Qaidam Basin (China). In this study, we analyzed well samples with X-ray diffraction (XRD), nuclear magnetic resonance (NMR), and mercury injection capillary pressure (MICP) data in integration with scanning electron microscopy (SEM) images to decipher the mineral composition and pore structure characteristics of the Xiaganchaigou Formation. We also calculate the fractal dimensions using MICP, NMR T2 spectrum, and SEM images based on fractal theory models. The results indicate that the mixed siliciclastic-carbonate samples of the upper section of the Xiaganchaigou Formation are mainly formed by dolomite and clay minerals with low siliceous and calcite content. Porosity is relatively low (2.01−9.83%) and positively correlated with dolomite content, thus indicating that the dolomite intercrystalline pores formed by infiltration and reflux dolomitization control the reservoir characteristics. The size of dolomite intercrystalline pores varies between several and hundreds of nanometers. The porosity has a poor correlation with permeability, which indicates that the pores are mostly primary, which lack the transformation of late dissolution. Three types of mixed siliciclastic-carbonate reservoirs are identified according to pore size distribution (<20 nm, 20−300 nm and multiple distribution), calculated using the NMR T2 spectrum. Fractal curves calculated by combining the MICP and NMR data are characterized by multisegments. The number of segments depends on the degree of heterogeneity of pore structure: two segment for high heterogeneity and three segment for low heterogeneity, also indicating a multifractal feature in mixed rock reservoirs. There is a negative correlation trend between porosity and fractal dimensions, and larger pores often have larger fractal dimensions. These results show that MICP-based fractal values are higher than those of NMR-based, which result from unconnected pores that the MICP is unable to reach. Fractal dimensions obtained from SEM have a small and narrow distribution range and are negatively correlated with the number of pores with smaller sizes. In essence, this study shows that the fractal dimension can be a concise index to evaluate the heterogeneity of lacustrine mixed siliciclastic-carbonate reservoirs, which can serve as an important reference for hydrocarbon development plans.\",\"PeriodicalId\":22066,\"journal\":{\"name\":\"SPE Reservoir Evaluation & Engineering\",\"volume\":\"78 1\",\"pages\":\"\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2023-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SPE Reservoir Evaluation & Engineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.2118/215839-pa\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENERGY & FUELS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SPE Reservoir Evaluation & Engineering","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.2118/215839-pa","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
Pore Structure and Fractal Characteristics of Mixed Siliciclastic-Carbonate Rocks from the Yingxi Area, Southwest Qaidam Basin, China
Evaluating reservoir properties at the pore scale is vital to better estimate hydrocarbon reserves and plan field development. The lacustrine mixed siliciclastic-carbonate deposits of the Upper Paleogene Xiaganchaigou Formation in the west Yingxiongling area form one of the most important hydrocarbon reservoirs in the southwestern Qaidam Basin (China). In this study, we analyzed well samples with X-ray diffraction (XRD), nuclear magnetic resonance (NMR), and mercury injection capillary pressure (MICP) data in integration with scanning electron microscopy (SEM) images to decipher the mineral composition and pore structure characteristics of the Xiaganchaigou Formation. We also calculate the fractal dimensions using MICP, NMR T2 spectrum, and SEM images based on fractal theory models. The results indicate that the mixed siliciclastic-carbonate samples of the upper section of the Xiaganchaigou Formation are mainly formed by dolomite and clay minerals with low siliceous and calcite content. Porosity is relatively low (2.01−9.83%) and positively correlated with dolomite content, thus indicating that the dolomite intercrystalline pores formed by infiltration and reflux dolomitization control the reservoir characteristics. The size of dolomite intercrystalline pores varies between several and hundreds of nanometers. The porosity has a poor correlation with permeability, which indicates that the pores are mostly primary, which lack the transformation of late dissolution. Three types of mixed siliciclastic-carbonate reservoirs are identified according to pore size distribution (<20 nm, 20−300 nm and multiple distribution), calculated using the NMR T2 spectrum. Fractal curves calculated by combining the MICP and NMR data are characterized by multisegments. The number of segments depends on the degree of heterogeneity of pore structure: two segment for high heterogeneity and three segment for low heterogeneity, also indicating a multifractal feature in mixed rock reservoirs. There is a negative correlation trend between porosity and fractal dimensions, and larger pores often have larger fractal dimensions. These results show that MICP-based fractal values are higher than those of NMR-based, which result from unconnected pores that the MICP is unable to reach. Fractal dimensions obtained from SEM have a small and narrow distribution range and are negatively correlated with the number of pores with smaller sizes. In essence, this study shows that the fractal dimension can be a concise index to evaluate the heterogeneity of lacustrine mixed siliciclastic-carbonate reservoirs, which can serve as an important reference for hydrocarbon development plans.
期刊介绍:
Covers the application of a wide range of topics, including reservoir characterization, geology and geophysics, core analysis, well logging, well testing, reservoir management, enhanced oil recovery, fluid mechanics, performance prediction, reservoir simulation, digital energy, uncertainty/risk assessment, information management, resource and reserve evaluation, portfolio/asset management, project valuation, and petroleum economics.