{"title":"致密砂岩中单峰核磁共振 T2 分布的渗透率预测模型:中国莺歌海盆地黄流地层案例研究","authors":"Jing Zhao, Zhilong Huang, Jin Dong, Jingyuan Zhang, Rui Wang, Chonglin Ma, Guangjun Deng, Maguang Xu","doi":"10.1007/s11004-023-10118-1","DOIUrl":null,"url":null,"abstract":"<p>Tight sandstone reservoirs have low porosity, low permeability, and a complex pore structure. The seepage from tight sandstones is a key factor in evaluating the oil and gas accumulation in these reservoirs. Therefore, reservoir permeability prediction has become the focus of researchers. Using nuclear magnetic resonance (NMR), high-pressure mercury injection, scanning electron microscopy, and other experimental methods, scholars have established various permeability prediction models, which have obvious advantages and disadvantages. However, there is less research conducted on predicting the permeability of tight sandstone reservoirs according to their single-peak NMR <i>T</i><sub>2</sub> distribution. Based on NMR experiments and the bimodal Gaussian density formula, this study identified the criteria for determining the types of reservoir pore structures with single-peak NMR <i>T</i><sub>2</sub> distribution and established the parameters (<i>η</i><sub>1</sub> and <i>η</i><sub>2</sub>) that can be used in the evaluation of reservoir pore structure. A novel model for predicting the permeability of tight sandstone reservoirs was established using <i>η</i><sub>1</sub> and <i>η</i><sub>2</sub>. The results of the prediction model proposed in this study were found to be superior to the results of eight permeability prediction models established by other scholars in the studied case of the Huangliu Formation. However, permeability prediction models established using the NMR experimental results of different sources were found to be ineffective. Additionally, the new model is suitable for use with sandstone reservoirs with both single-peak and double-peak NMR <i>T</i><sub>2</sub> distributions in the studied case of the Yanchang Formation. Logging curves can be used to predict <i>η</i><sub>1</sub> and <i>η</i><sub>2</sub>, and the permeability of a single well of a tight sandstone reservoir. The study findings would be useful for predicting tight sandstone reservoir permeability.</p>","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2024-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Permeability Prediction Model of Single-Peak NMR T2 Distribution in Tight Sandstones: A Case Study on the Huangliu Formation, Yinggehai Basin, China\",\"authors\":\"Jing Zhao, Zhilong Huang, Jin Dong, Jingyuan Zhang, Rui Wang, Chonglin Ma, Guangjun Deng, Maguang Xu\",\"doi\":\"10.1007/s11004-023-10118-1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Tight sandstone reservoirs have low porosity, low permeability, and a complex pore structure. The seepage from tight sandstones is a key factor in evaluating the oil and gas accumulation in these reservoirs. Therefore, reservoir permeability prediction has become the focus of researchers. Using nuclear magnetic resonance (NMR), high-pressure mercury injection, scanning electron microscopy, and other experimental methods, scholars have established various permeability prediction models, which have obvious advantages and disadvantages. However, there is less research conducted on predicting the permeability of tight sandstone reservoirs according to their single-peak NMR <i>T</i><sub>2</sub> distribution. Based on NMR experiments and the bimodal Gaussian density formula, this study identified the criteria for determining the types of reservoir pore structures with single-peak NMR <i>T</i><sub>2</sub> distribution and established the parameters (<i>η</i><sub>1</sub> and <i>η</i><sub>2</sub>) that can be used in the evaluation of reservoir pore structure. A novel model for predicting the permeability of tight sandstone reservoirs was established using <i>η</i><sub>1</sub> and <i>η</i><sub>2</sub>. The results of the prediction model proposed in this study were found to be superior to the results of eight permeability prediction models established by other scholars in the studied case of the Huangliu Formation. However, permeability prediction models established using the NMR experimental results of different sources were found to be ineffective. Additionally, the new model is suitable for use with sandstone reservoirs with both single-peak and double-peak NMR <i>T</i><sub>2</sub> distributions in the studied case of the Yanchang Formation. Logging curves can be used to predict <i>η</i><sub>1</sub> and <i>η</i><sub>2</sub>, and the permeability of a single well of a tight sandstone reservoir. The study findings would be useful for predicting tight sandstone reservoir permeability.</p>\",\"PeriodicalId\":2,\"journal\":{\"name\":\"ACS Applied Bio Materials\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2024-01-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Bio Materials\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.1007/s11004-023-10118-1\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MATERIALS SCIENCE, BIOMATERIALS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1007/s11004-023-10118-1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
A Permeability Prediction Model of Single-Peak NMR T2 Distribution in Tight Sandstones: A Case Study on the Huangliu Formation, Yinggehai Basin, China
Tight sandstone reservoirs have low porosity, low permeability, and a complex pore structure. The seepage from tight sandstones is a key factor in evaluating the oil and gas accumulation in these reservoirs. Therefore, reservoir permeability prediction has become the focus of researchers. Using nuclear magnetic resonance (NMR), high-pressure mercury injection, scanning electron microscopy, and other experimental methods, scholars have established various permeability prediction models, which have obvious advantages and disadvantages. However, there is less research conducted on predicting the permeability of tight sandstone reservoirs according to their single-peak NMR T2 distribution. Based on NMR experiments and the bimodal Gaussian density formula, this study identified the criteria for determining the types of reservoir pore structures with single-peak NMR T2 distribution and established the parameters (η1 and η2) that can be used in the evaluation of reservoir pore structure. A novel model for predicting the permeability of tight sandstone reservoirs was established using η1 and η2. The results of the prediction model proposed in this study were found to be superior to the results of eight permeability prediction models established by other scholars in the studied case of the Huangliu Formation. However, permeability prediction models established using the NMR experimental results of different sources were found to be ineffective. Additionally, the new model is suitable for use with sandstone reservoirs with both single-peak and double-peak NMR T2 distributions in the studied case of the Yanchang Formation. Logging curves can be used to predict η1 and η2, and the permeability of a single well of a tight sandstone reservoir. The study findings would be useful for predicting tight sandstone reservoir permeability.