Spectral decomposition technique was applied in tunnel identification of coal mine.Spectrum decomposition was worked on a 3D seismic data,and many tuning data volume at different frequency could be obtained.In the full analysis of the small goaf tunnel based on the tuning frequency,the authors chose the frequency which is a little higher than the tuning frequency to extract the amplitude attribute of this volume,and the characteristic of the anomalies was also analyzed.The variance cube technology was used on the single frequency 3D seismic data which is the result of spectrum decomposition,then extract the amplitude attribute,the results of this kind of data have both the advantages of spectrum decomposition and variance cube technology,the final result is better to identify the anomalies.By using this method of 3D seismic data,the authors eventually identified the goaf tunnels in the small coal mine.Actual drilling data showed that three of the drill holes were drilled in the tunnels of small coal mine,and totally pumped out 100 000 m3 water from the tunnel.The interpretation data provides good effect for the coal safety mining,and also proved this method of prediction in tunnel identification is very useful.%将谱分解技术应用于小窑采空巷道的识别当中,对三维地震资料进行频谱分解,得到不同频率的调谐数据体.在充分分析小窑采空巷道的调谐频率基础上,选择略高于调谐频率的单频数据体进行属性提取,分析单频率下的异常特征.采用方差体技术对频谱分解后的单频率数据体进行方差计算,再提取振幅属性进行分析,该结果同时具有频谱分解和方差体结果的优势,有利于分析构造异常.采用该法对三维地震资料进行分析,预测了小窑采空巷道的平面位置.实际钻探验证资料表明,在所预测的小窑巷道布设的3个钻孔均钻遇小窑巷道,共抽水10万m3,为煤矿安全开采提供了地质依据,也说明了该方法在小窑预测方面的优势.
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