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《Coal Geology & Exploration》 2011-02
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Relationship between approximate analysis of coal and log parameters and its models

MENG Zhaoping1,2,ZHU Shaojun 1,3,JIA Lilong1,SHEN Hengming1(1.College of Geosciences and Surveying Engineering,China University of Mining and Technology, Beijing 100083,China;2.Key Laboratory of Geological Hazards on Three Gorges Reservoir Area, Ministry of Education,China Three Gorges University,Yichang 443002,China;3.The First Team of Coal Geology Bureau of Henan Province,Xinzheng 451150,China)  
The main indicator of raw coal quality evaluation is approximate analysis.Based on Zhaojiazhai coal field of Xinzheng mine area in Henan province,through the testing and statistical analysis,the relationship between coal approximate analysis and log parameters and its models have been established,and the logging response mechanism of coal quality was studied.The results show that between approximate analysis and log parameters exists an obvious correlation.There is the negative correlation between the moisture content of raw coal and the apparent resistivity and density,and the positive correlation between the moisture content of raw coal and the natural potential and natural gamma.The ash content of raw coal has a positive corelation with density,natural gamma and natural potential respectively,and a negative correlation with apparent resistivity.There is a negative correlation between the volatile of raw coal and apparent resistivity and density,and a positive corelation between the volatile of raw coal and natural potential and natural gamma.The correlation between the coal quality indica-tors and the log parameters is determined by the content of organic matter and inorganic matter in coal,the coal property,the coal structure,the coalification and other factors.The multi-statistical models were established re-spectively through logging curves predicting parameters for approximate analysis.In the process of exploring coal and coal bed methane,the purpose of predicting the parameters for approximate analysis can be realized by using logging curves.
【Fund】: 国家自然科学基金项目(40772100 41030422);; 国家重点基础研究发展计划(973计划)项目(2007CB209405);; 教育部高等学校博士学科点专项科研基金项目(20100023110003);; 煤炭资源与安全开采国家重点实验室课题(SKLCRSM10806)
【CateGory Index】: P618.11
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