【摘要】 水平叠加技术能够有效地压制随机噪声和多次波,但是对于由于相邻道的噪声表现出相关性和一致性而产生的某些相干干扰,常规的叠加技术容易产生假的同相轴,难以取得较高的信噪比.基于小波理论和高阶统计理论本文提出了小波域高阶相关叠加技术(HOCS),其基本原理是将经动静校正的CMP道集变换到小波域,然后在小波域求取高阶相关系数,进而加权叠加.数值实验和实际资料计算的结果表明,此方法比常规叠加更能够有效地提高信噪比,剔除常规加权叠加无法抑制的某些相关噪声.更多还原

【Abstract】 The horizontal stacking plays an important role in processing seismic data digitally, due to its efficiency in suppressing random noise and multiplies. However,for some noise exhibiting coherence and correlation in adjacent traces, the weighted stacking based on the conventional correlative function always leads to false events and lower ratios of signal to noise(S/N). In this paper, a new method of higher_order correlative stacking (HOCS) is proposed in the light of the theory of wavelet and higher_order statistics. The main idea is to stack common midpoint gathers after the normal movemout, according to the weight that is calculated on the basis of the higher_order correlative function in the wavelet domain. The results of both synthetic and practical examples show the advantages in improving S/N and muting some correlative noise that the conventional stacking can not inhibit.更多还原