Journal of Jilin University(Earth Science Edition) ›› 2022, Vol. 52 ›› Issue (2): 633-643.doi: 10.13278/j. cnki.jjuese.20210139

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Log Response of Coal Quality and Its Prediction Model in Renjiazhuang Coal Mine#br#

Wu Meng1,2, Qin Yunhu1, Wang Xiaoqing3, Yang Liu4, Zhu Shifei1, Zhang Zhen2, Mao Lixin1, Zhang Jing1, Li Guozhang5#br#   

  1. 1. Jiangsu Mineral Resources and Geological Design and Research Institute, Xuzhou 221006, Jiangsu, China
    2. Key Laboratory of Coalbed Methane Resources &  Reservoir Formation Process, Ministry of Education, 
    Xuzhou 221008, Jiangsu, China
    3. School of Environment and Spatial Informatics, China University of Mining and Technology, 
    Xuzhou 221116, Jiangsu, China
    4. School of Construction Management, Jiangsu Vocational Institute of Architectural Technology, Xuzhou 221116, Jiangsu, China
    5. Department of Geological Engineering, Qinghai University, Xining 810016, China

  • Received:2021-05-06 Online:2022-03-27 Published:2022-11-22
  • Supported by:
    the National Science and Technology Major Project of China (2016ZX050660104), the Science and Technology Project of China National Administration of coal Geology (ZMKJ-2019-J13), the Key Social Development Project of Xuzhou Science and Technology Bureau (KC21147) and the Science and Technology Fund of Jiangsu Mineral Resources and Geological Design and Research Institute (JSY2020-6)

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Abstract: The logging response research of coal seam and coal quality is of great significance to the precise mining of coal and the exploration and development of coalbed methane. Taking a coal seam of  Taiyuan Formation in Renjiazhuang coal mine in Ningxia as an example, the correlation of coal quality logging response was analyzed by means of experimental test, statistical analysis, and data test. The results show that moisture and volatile matter in coal are negatively correlated with lateral resistivity, and positively correlated with spontaneous potential, natural gamma value, and short source distance gamma-gamma value. Ash content is negatively correlated with short source distance gamma-gamma value and lateral resistivity, and positively correlated with natural gamma value and spontaneous potential. Fixed carbon has a positive correlation with short source distance gamma-gamma value and lateral resistivity, and a negatively correlation with natural gamma value and spontaneous potential. Based on the analysis, a multivariate prediction model of coal seam logging parameters is established. F-function test and experimental sample prediction show that the model can better serve coal mining.

Key words: Renjiazhuang coalmine, Taiyuan Formation, coal quality, logging response, prediction model

CLC Number: 

  • P631.8
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