由于储层介质具有黏滞性，地震波在穿过含油气地层时会产生强烈的吸收衰减，并在储层下方产生低频伴影异常，因此，这种异常可以作为一种直接检测烃类的方法。 深层碳酸盐岩储层内部结构复杂，地震资料分辨率低，用常规时频分析方法难以精确刻画储层内部结构。 针对这些问题提出了一种基于匹配追踪算法的碳酸盐岩储层低频伴影识别方法，该方法利用匹配追踪算法对地震资料进行谱分解。 通过与其他时频分析方法进行对比，表明该方法具有更高的时频分辨率，能够有效检测储层低频伴影异常。 实际资料试算表明，基于匹配追踪算法的低频伴影方法能够有效检测深层碳酸盐岩含气储层。

  This paper focused on the low-frequency shadow caused by the attenuation by absorption of seismic waves in viscous media, which can be used as a hydrocarbon indicator. It is very difficult to detect the low-frequency shadow in deep carbonate reservoir by conventional time-frequency analysis methods, due to the poor seismic resolution resulted by the complex inner structure in stratigraphic and lithologic traps. A new matching pursuit algorithm based low-frequency shadow method for carbonate reservoir characterization was introduced. This paper described the low frequency shadow and the principle of matching pursuit algorithm based on spectral decomposition of seismic signal, and showed that the method has high time-frequency resolution compared with others and it can be used to predict the deep carbonate reservoir. The well drilling data proved the good prediction efforts.