相似度加权的超虚干涉法加强初至波信号

Similarity-Weighted Super-Virtual Interferometry to Enhance First Breaks

当低信噪比资料局部道集存在强噪声时,超虚干涉法虽然能够提高远偏移距折射波初至的信噪比,但可能降低临近道集的初至信噪比。为解决这一问题,提出基于相似度加权叠加的超虚干涉法。通过互相关和褶积运算,实现相邻道包含的初至波信号的同相位叠加,达到提高信噪比的目的;同时,引入相似度权重函数,提高压制局部异常噪声的能力。合成数据和实际数据实例都说明所提方法能有效地提高地震初至波信噪比。最后,讨论了方法的抗噪性和适用性。

When strong noise exists on local seismic traces with low signal-to-noise ratio （SNR）, super-virtual interferometry （SVI） method can be used to increase the SNR of first breaks on far-offset traces, but may decrease the SNR of first breaks around the noisy traces. To solve this problem, the similarity-weighted super-virtual interferometry is developed. Correlation and convolution are applied to stack the first arrivals on neighboring traces in common phase, and consequently increase the SNR of first arrivals. The introduction of similarity-weighted function improves the ability to suppress strong local abnormal noise. Both the synthetic and field data examples demonstrate the effectiveness of the proposed method to enhance seismic first breaks. At last, a discussion about the applicabilities and the anti-noise abilities of the proposed method is included.