Open AccessApplication of Multi-group Seam Thickness Prediction in CJT Coal Mine
Author(s) -
Rui Shan
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/525/1/012091
Subject(s) - coal mining , coal , inversion (geology) , mining engineering , geology , correlation coefficient , petroleum engineering , soil science , seismology , computer science , engineering , machine learning , tectonics , waste management
Accurate prediction of coal thickness is of great significance to guide coal mine safety production. Taking the coal thickness prediction of the CJT coalfield in shaanxi province as an example, this paper selects the conventional wave impedance inversion technology and seismic multi-attribute technology to comprehensively predict the thickness of the target coal seam, and the correlation coefficient of the prediction trend of the coal seam thickness is as high as 98%. The prediction results show that wave impedance inversion combined with multi-attribute quantitative prediction of coal seam thickness is an effective method for complex geological conditions in the study area.