M. Elsayed, A. El-Husseiny, S. R. Hussaini, Hani Al Mukainah, Mohamed Mahmoud
{"title":"粘土分布和矿物学对核磁共振T2和内部梯度影响的实验研究:来自良好控制的物理样品的见解","authors":"M. Elsayed, A. El-Husseiny, S. R. Hussaini, Hani Al Mukainah, Mohamed Mahmoud","doi":"10.2118/212300-pa","DOIUrl":null,"url":null,"abstract":"\n Nuclear magnetic resonance (NMR) is a reliable tool for petrophysical evaluation and the characterization of pore structures. Compared to conventional carbonate reservoirs, sandstone reservoirs contain higher amounts of ferromagnetic and paramagnetic ions (such as iron, nickel, or manganese) usually found in microporous clay aggregates. The interpretation of petrophysical data in sandstone formations can be complicated by variations in clay mineralogy and distribution patterns (laminated, structural, and dispersed). Nevertheless, the impact of clay distribution patterns on NMR signals is not well understood. This study aims to investigate the impact of clay mineralogy and distribution patterns on the T2 relaxation times and internal gradient (i.e., inhomogeneity in the magnetic field). Glass beads were mixed with three different clay minerals characterized by no iron content (kaolinite) to higher iron content (illite and nontronite). The bead-clay mixtures were prepared at a fixed clay content but with variable clay distribution patterns to examine the impact of clay distribution alone. NMR T2 measurements at several echo times were performed on the pure glass beads and the mixtures to evaluate how clay mineralogy and distribution patterns affect the T2 and the internal gradient of the host glass beads. At a given clay distribution pattern, a more significant decrease in T2 relaxation times and a larger increase in the internal gradient of glass beads were observed when adding clays with higher iron content. This is explained by the higher surface relaxivity, and magnetic susceptibility caused when introducing clay with higher iron content. Such an impact can complicate the characterization of NMR-derived pore sizes as similar pore size distribution (PSD) can have very different T2 distribution and the logarithmic mean of T2 relaxation time distribution (T2LM) values. Micro-computed tomography (µCT) images were acquired to compute the PSD to compare it with ones obtained from the NMR measurements. The PSD for the three clay minerals showed almost the same distribution using µCT; however, they showed totally different T2 relaxation times distributions. That is due to the significant impact of the internal gradient causing a distortion in the magnetic field. Thus, careful consideration must be taken before converting the NMR data into PSD. The introduction of iron-free kaolinite resulted in a negligible impact on the internal gradient of glass beads regardless of the clay distribution pattern. On the other hand, the addition of dispersed iron-rich clays (illite and nontronite) results in up to two orders of magnitude increase in internal gradients, compared to mixtures with laminated and structural clays (at the same clay mineralogy and content). Moreover, dispersed clay mixtures display larger changes in T2LM and porosity as a function of increasing echo time. The results from this study suggest that changes in T2LM and the logarithmic mean of the effective internal gradient distribution geff,LM, compared to the clean host sand, can provide insight into iron-rich clay distribution. Larger changes in any given clay content and mineralogy would suggest a more dominant dispersed clay distribution while negligible changes would suggest a laminated distribution.","PeriodicalId":22066,"journal":{"name":"SPE Reservoir Evaluation & Engineering","volume":null,"pages":null},"PeriodicalIF":2.1000,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Experimental Study on the Impact of Clay Distribution and Mineralogy on NMR T2 and Internal Gradient: Insights From Well-Controlled Physical Samples\",\"authors\":\"M. Elsayed, A. El-Husseiny, S. R. Hussaini, Hani Al Mukainah, Mohamed Mahmoud\",\"doi\":\"10.2118/212300-pa\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n Nuclear magnetic resonance (NMR) is a reliable tool for petrophysical evaluation and the characterization of pore structures. Compared to conventional carbonate reservoirs, sandstone reservoirs contain higher amounts of ferromagnetic and paramagnetic ions (such as iron, nickel, or manganese) usually found in microporous clay aggregates. The interpretation of petrophysical data in sandstone formations can be complicated by variations in clay mineralogy and distribution patterns (laminated, structural, and dispersed). Nevertheless, the impact of clay distribution patterns on NMR signals is not well understood. This study aims to investigate the impact of clay mineralogy and distribution patterns on the T2 relaxation times and internal gradient (i.e., inhomogeneity in the magnetic field). Glass beads were mixed with three different clay minerals characterized by no iron content (kaolinite) to higher iron content (illite and nontronite). The bead-clay mixtures were prepared at a fixed clay content but with variable clay distribution patterns to examine the impact of clay distribution alone. NMR T2 measurements at several echo times were performed on the pure glass beads and the mixtures to evaluate how clay mineralogy and distribution patterns affect the T2 and the internal gradient of the host glass beads. At a given clay distribution pattern, a more significant decrease in T2 relaxation times and a larger increase in the internal gradient of glass beads were observed when adding clays with higher iron content. This is explained by the higher surface relaxivity, and magnetic susceptibility caused when introducing clay with higher iron content. Such an impact can complicate the characterization of NMR-derived pore sizes as similar pore size distribution (PSD) can have very different T2 distribution and the logarithmic mean of T2 relaxation time distribution (T2LM) values. Micro-computed tomography (µCT) images were acquired to compute the PSD to compare it with ones obtained from the NMR measurements. The PSD for the three clay minerals showed almost the same distribution using µCT; however, they showed totally different T2 relaxation times distributions. That is due to the significant impact of the internal gradient causing a distortion in the magnetic field. Thus, careful consideration must be taken before converting the NMR data into PSD. The introduction of iron-free kaolinite resulted in a negligible impact on the internal gradient of glass beads regardless of the clay distribution pattern. On the other hand, the addition of dispersed iron-rich clays (illite and nontronite) results in up to two orders of magnitude increase in internal gradients, compared to mixtures with laminated and structural clays (at the same clay mineralogy and content). Moreover, dispersed clay mixtures display larger changes in T2LM and porosity as a function of increasing echo time. The results from this study suggest that changes in T2LM and the logarithmic mean of the effective internal gradient distribution geff,LM, compared to the clean host sand, can provide insight into iron-rich clay distribution. Larger changes in any given clay content and mineralogy would suggest a more dominant dispersed clay distribution while negligible changes would suggest a laminated distribution.\",\"PeriodicalId\":22066,\"journal\":{\"name\":\"SPE Reservoir Evaluation & Engineering\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2022-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SPE Reservoir Evaluation & Engineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.2118/212300-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/10.2118/212300-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}
Experimental Study on the Impact of Clay Distribution and Mineralogy on NMR T2 and Internal Gradient: Insights From Well-Controlled Physical Samples
Nuclear magnetic resonance (NMR) is a reliable tool for petrophysical evaluation and the characterization of pore structures. Compared to conventional carbonate reservoirs, sandstone reservoirs contain higher amounts of ferromagnetic and paramagnetic ions (such as iron, nickel, or manganese) usually found in microporous clay aggregates. The interpretation of petrophysical data in sandstone formations can be complicated by variations in clay mineralogy and distribution patterns (laminated, structural, and dispersed). Nevertheless, the impact of clay distribution patterns on NMR signals is not well understood. This study aims to investigate the impact of clay mineralogy and distribution patterns on the T2 relaxation times and internal gradient (i.e., inhomogeneity in the magnetic field). Glass beads were mixed with three different clay minerals characterized by no iron content (kaolinite) to higher iron content (illite and nontronite). The bead-clay mixtures were prepared at a fixed clay content but with variable clay distribution patterns to examine the impact of clay distribution alone. NMR T2 measurements at several echo times were performed on the pure glass beads and the mixtures to evaluate how clay mineralogy and distribution patterns affect the T2 and the internal gradient of the host glass beads. At a given clay distribution pattern, a more significant decrease in T2 relaxation times and a larger increase in the internal gradient of glass beads were observed when adding clays with higher iron content. This is explained by the higher surface relaxivity, and magnetic susceptibility caused when introducing clay with higher iron content. Such an impact can complicate the characterization of NMR-derived pore sizes as similar pore size distribution (PSD) can have very different T2 distribution and the logarithmic mean of T2 relaxation time distribution (T2LM) values. Micro-computed tomography (µCT) images were acquired to compute the PSD to compare it with ones obtained from the NMR measurements. The PSD for the three clay minerals showed almost the same distribution using µCT; however, they showed totally different T2 relaxation times distributions. That is due to the significant impact of the internal gradient causing a distortion in the magnetic field. Thus, careful consideration must be taken before converting the NMR data into PSD. The introduction of iron-free kaolinite resulted in a negligible impact on the internal gradient of glass beads regardless of the clay distribution pattern. On the other hand, the addition of dispersed iron-rich clays (illite and nontronite) results in up to two orders of magnitude increase in internal gradients, compared to mixtures with laminated and structural clays (at the same clay mineralogy and content). Moreover, dispersed clay mixtures display larger changes in T2LM and porosity as a function of increasing echo time. The results from this study suggest that changes in T2LM and the logarithmic mean of the effective internal gradient distribution geff,LM, compared to the clean host sand, can provide insight into iron-rich clay distribution. Larger changes in any given clay content and mineralogy would suggest a more dominant dispersed clay distribution while negligible changes would suggest a laminated distribution.
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.