Accurate prediction of magmatic intrusion into a coal bed is illustrated using the method of seismic spectral decomposition.The characteristics of coal seismic reflections are first analyzed and the effect of variable time windows and domain frequencies on the spectral decomposition are examined.The higher domain frequency of coal bed reflections using the narrower STFT time window,or the smaller ST scale factor,are acceptable.When magmatic rock intrudes from the bottom of the coal bed the domain frequency of the reflections is decreased slightly,the frequency bandwidth is narrowed correspondingly,and the response from spectral decomposition is significantly reduced.Intrusion by a very thin magmatic rock gives a spectral decomposition response that is just slightly less than what is seen from a normal coal bed.Results from an actual mining area were used to validate the method.Predicting the boundary of magmatic intrusions with the method discussed herein was highly accurate and has been validated by observations from underground mining.
Goafs are threats to safe mining.Their imaging effects or those of other complex geological bodies are often poor in conventional reflected wave images.Hence,accurate detection of goafs has become an important problem,to be solved with a sense of urgency.Based on scattering theory,we used an equivalent offset method to extract Common Scattering Point gathers,in order to analyze different scattering wave characteristics between Common Scattering Point and Common Mid Point gathers and to compare stack and migration imaging effects.Our research results show that the scattering wave imaging method is more efficient than the conventional imaging method and is therefore a more effective imaging method for detecting goafs and other complex geological bodies.It has important implications for safe mining procedures and infrastructures.
Li JuanjuanPan DongmingLiao TaipingHu MingshunWang Linlin
