Open AccessComposite Advanced Detection for Coal Seam Thickness in Coal Roadway
Author(s) -
Bo Wang,
Xiayang Zhang,
Shengdong Liu,
Lu Tuo,
Chen Mulan
Publication year - 2015
Publication title -
the open petroleum engineering journal
Language(s) - English
Resource type - Journals
ISSN - 1874-8341
DOI - 10.2174/1874834101508010153
Subject(s) - coal mining , wavelet , joint (building) , mining engineering , deformation (meteorology) , geology , coal , engineering , field (mathematics) , geotechnical engineering , structural engineering , computer science , artificial intelligence , oceanography , mathematics , pure mathematics , waste management
The thickness change of coal seam can be resulted from several reasons, like primary sedimentary environmentand later tectonic deformation. The thickness change ahead of driving face may have an impact on the efficiency andsafety of the mining progress, thus the advanced prediction of seam thickness is important. However, it is hard to predictthe seam thickness with a single advanced detection method. This paper combines three methods, e.g., MSP, MRP, andMTEM to perform a joint detection, and makes data fusion through wavelet analysis, which makes use of the elastic wavefield and geo-electrical field characteristics. A field test indicates that the prediction of seam thickness by means of integratedadvanced detection is approximately accurate with an error less than 5%.