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针对多分量地震数据具有信噪比低、波场比较复杂等特点,同时为了解决有效波和面波在低频带具有相关性且频带有重叠的部分.本文基于希尔伯特—黄变换(Hilbert—Huang transform,HHT)提出一种多分量地震数据去噪方法.HHT的核心部分是固有模态分解(Empirical mode composition method,EMD),它将地震信号自适应分解为各个尺度的固有模态函数(Intrinsic mode function,IMF);然后根据有效波和噪声分布在不同的分辨尺度范围内进行数据重构;对于一些尺度分布比较宽的,进行更加严格的EMD分解,以及通过瞬时参数阈值大小进行处理以达到更好的去噪效果.本文所做的工作主要针对多波资料中面波的处理,利用面波跟有效波的频率尺度和瞬时属性差异,从仿真数据、模型和实际地震数据进行面波的压制实验,取得了比较满意的压制效果,提高了地震资料的分辨率.也表明了该方法在多分量地震去噪处理中的可行性.
For the multi-component seismic data with low signal-to-noise ratio, the wave field is more complex and so on, at the same time in order to solve the effective wave and surface wave in the low frequency band has a correlation and frequency band overlap.This paper based on the Hilbert - -Huang transform, HHT) proposed a multi-component seismic data denoising method.The core part of HHT is the EMD (in-situ modal decomposition method), which decomposes the seismic signal into the intrinsic mode functions of various scales (Intrinsic mode function, IMF). Then the data reconstructions are performed according to the effective wave and the noise distribution in different resolution scales. For some wide-scale distributions, the more rigorous EMD decomposition is performed and the threshold value of the instantaneous parameter is used for processing In order to achieve a better denoising effect.The work done in this paper is mainly dealing with surface wave in multi-wave data, using the frequency scale and instantaneous property difference of surface wave and effective wave, the surface data from the simulation data, the model and the actual seismic data Wave suppression experiments have been made more satisfactory suppression effect and improve the resolution of seismic data also shows that the method of multi-component The feasibility of de-noising processing.