Volume 46 Issue S1
Jul.  2018
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LIU Zuiliang, LUO Zhongqin. Predict the lithology of coalbed roof with probability neural network inversion use Sijiazhuang coalmine as an example[J]. COAL GEOLOGY & EXPLORATION, 2018, 46(S1): 50-55. DOI: 10.3969/j.issn.1001-1986.2018.S1.011
Citation: LIU Zuiliang, LUO Zhongqin. Predict the lithology of coalbed roof with probability neural network inversion use Sijiazhuang coalmine as an example[J]. COAL GEOLOGY & EXPLORATION, 2018, 46(S1): 50-55. DOI: 10.3969/j.issn.1001-1986.2018.S1.011
shu

Predict the lithology of coalbed roof with probability neural network inversion use Sijiazhuang coalmine as an example

  • 1. Geological Survey Department, Yangquan Coal Industry(GROUP) Co. Ltd., Yangquan 045000, China;

  • 2. Research Institute of Coal Geophysical Exploration of China national Administration of coal geology, Hebei Baoding 072750, China

Funds: 

National Science and Technology Major Project(2016ZX05041, 2016ZX05043)

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  • Received Date: May 30, 2018
  • Published Date: July 24, 2018
    Graphical Abstract
    • Abstract
  • In order to study the trend of structural soft coal in Sijiazhuang coal mine, the PNN neural network inversion technique is used to invert the lithology of coal seam roof in the study area, so as to predict the structure of soft coal. Taking natural gamma curve as a constraint condition, by analyzing the response characteristics of the sandstone, mudstone density and gamma ray of the target area, the PNN inversion of the post stack 3D seismic data is carried out. The results show that the roof sandstone of No. 15 coal seam corresponds to low natural gamma value and positively correlated with the development of structural soft coal. By studying the distribution law of sandstone in coal seam roof, the spatial development characteristics of tectonic soft coal can be indirectly predicted.
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    • References (13)
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