Pore structure characterization and permeability prediction of coal samples based on SEM images

doi:10.1016/j.jngse.2019.05.003

CORC > 武汉岩土力学研究所 > 中科院武汉岩土力学所 > 岩土力学所知识全产出 > 期刊论文

	Pore structure characterization and permeability prediction of coal samples based on SEM images
	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
	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
内容类型	期刊论文
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
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.