The thickness change of coal seam can be resulted from several reasons, like primary sedimentary environment
and later tectonic deformation. The thickness change ahead of driving face may have an impact on the efficiency and
safety of the mining progress, thus the advanced prediction of seam thickness is important. However, it is hard to predict
the seam thickness with a single advanced detection method. This paper combines three methods, e.g., MSP, MRP, and
MTEM to perform a joint detection, and makes data fusion through wavelet analysis, which makes use of the elastic wave
field and geo-electrical field characteristics. A field test indicates that the prediction of seam thickness by means of integrated
advanced detection is approximately accurate with an error less than 5%.