Pore structure characterization and permeability prediction of coal samples based on SEM images
文献类型：期刊论文
| 作者 | Song, Shuai-Bing; Liu, Jiang-Feng; Yang, Dian-Sen; Ni, Hong-Yang; Huang, Bing-Xiang; Zhang, Kai; Mao, Xian-Biao |
| 刊名 | JOURNAL OF NATURAL GAS SCIENCE AND ENGINEERING
 |
| 出版日期 | 2019 |
| 卷号 | 67期号:-页码:160-171 |
| 关键词 | Gas permeability Pore size distribution SEM images Pore structure |
| ISSN号 | 1875-5100 |
| DOI | 10.1016/j.jngse.2019.05.003 |
| 英文摘要 | The pore structure of coal reservoirs determines the reserves of coalbed methane, and the gas permeability determines the level of the production capacity. In this study, the SEM images of coal samples were analyzed by various means. First, the grayscale threshold of binarization of the coal sample image is determined by a suitable algorithm. Comparing several different algorithms, the porosity based on Yen algorithm is closer to the results of vacuum saturation method and nuclear magnetic resonance (NMR) (8.35% vs. 7.51% vs. 8.92%). Further, the pore size distribution (PSD) of the coal sample is obtained according to discrete and continuous algorithms. By comparing the SEM results with the NMR results, it is found that the calculation results based on the continuous algorithm (CPSD) are better than the discrete algorithm (DPSD) and closer to the NMR results. For the effect of scale, we found that the image resolution has a certain influence on the minimum pore size characterized, such as sample Cl: 0.29 mu m ( x 1000) vs 0.58um ( x 500). At high resolution, more micro-pores are observed. Further, we predict the permeability of coal samples based on SEM images. It is found that the calculation results based on the continuous algorithm and the Hagen-Poiseuille equation are closer to the measured values (e.g., 16.97 (DPSD) vs. 0.45(CPSD) vs. 0.59 mD (Lab), sample C2, magnification of x 1000). In general, this method can effectively evaluate the pore structure characteristics and permeability of coal samples. |
| WOS研究方向 | Energy & Fuels ; Engineering |
| 语种 | 英语 |
| WOS记录号 | WOS:000471271600013 |
| 源URL | [http://119.78.100.198/handle/2S6PX9GI/14959]  |
| 专题 | 岩土力学所知识全产出_期刊论文 国家重点实验室知识产出_期刊论文 |
| 作者单位 | 1.China Univ Min & Technol, State Key Lab GeoMech & Deep Underground Engn, Xuzhou 221116, Jiangsu, Peoples R China; 2.China Univ Min & Technol, Sch Mech & Civil Engn, Xuzhou 221116, Jiangsu, Peoples R China; 3.Southwest Petr Univ, State Key Lab Oil & Gas Reservoir Geol & Exploita, Chengdu 610500, Sichuan, Peoples R China; 4.Chinese Acad Sci, Inst Rock & Soil Mech, State Key Lab Geomech & Geotech Engn, Wuhan 430071, Hubei, Peoples R China |
| 推荐引用方式 GB/T 7714 | Song, Shuai-Bing,Liu, Jiang-Feng,Yang, Dian-Sen,et al. Pore structure characterization and permeability prediction of coal samples based on SEM images[J]. JOURNAL OF NATURAL GAS SCIENCE AND ENGINEERING,2019,67(-):160-171. |
| APA | Song, Shuai-Bing.,Liu, Jiang-Feng.,Yang, Dian-Sen.,Ni, Hong-Yang.,Huang, Bing-Xiang.,...&Mao, Xian-Biao.(2019).Pore structure characterization and permeability prediction of coal samples based on SEM images.JOURNAL OF NATURAL GAS SCIENCE AND ENGINEERING,67(-),160-171. |
| MLA | Song, Shuai-Bing,et al."Pore structure characterization and permeability prediction of coal samples based on SEM images".JOURNAL OF NATURAL GAS SCIENCE AND ENGINEERING 67.-(2019):160-171. |
入库方式： OAI收割
来源：武汉岩土力学研究所
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