Multi-step damped multichannel singular spectrum analysis for simultaneous reconstruction and denoising of 3D seismic data
Multi-step damped multichannel singular spectrum analysis for simultaneous reconstruction and denoising of 3D seismic data
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DOI：
10.1088/1742-2132/13/5/704
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发表时间：
2016-08
影响因子：
1.4
通讯作者：
Dong Zhang;Yangkang Chen;Weilin Huang;S. Gan
中科院分区：
文献类型：
--
作者：
Dong Zhang;Yangkang Chen;Weilin Huang;S. Gan
多道奇异谱分析(MSSA)是一种同时进行地震数据重建和去噪的有效方法。MSSA使用截断奇异值分解(TSVD)将噪声信号分解为信号子空间和噪声子空间，并采用类似于POCS的加权凸集投影方法在每个频率片上重构适当构造的块Hankel矩阵中的缺失数据。然而，由于两个主要因素：传统TSVD的不足和在类POCS加权迭代过程中迭代插入的观测噪声数据，信号空间中仍然存在一些残留噪声。在本文中，我们首先将最近提出的用于随机噪声抑制的阻尼型MSSA(DMSSA)进一步扩展到同时重建和去噪，该方法对信号和噪声的区分能力更强。然后与DMSSA相结合，提出了一种多步策略--多步衰减MSSA(MS-DMSSA)，以有效地降低类POCS迭代过程中的插入噪声，从而提高同时重建和去噪的最终性能。MS-DMSSA方法在三维合成地震资料和野外地震资料上的应用表明，与传统的MSSA方法相比，该方法具有更好的性能。
Multichannel singular spectrum analysis (MSSA) is an effective approach for simultaneous seismic data reconstruction and denoising. MSSA utilizes truncated singular value decomposition (TSVD) to decompose the noisy signal into a signal subspace and a noise subspace and weighted projection onto convex sets (POCS)-like method to reconstruct the missing data in the appropriately constructed block Hankel matrix at each frequency slice. However, there still exists some residual noise in signal space due to two major factors: the deficiency of traditional TSVD and the iteratively inserted observed noisy data during the process of weighted POCS like iterations. In this paper, we first further extend the recently proposed damped MSSA (DMSSA) for random noise attenuation, which is more powerful in distinguishing between signal and noise, to simultaneous reconstruction and denoising. Then combined with DMSSA, we propose a multi-step strategy, named multi-step damped MSSA (MS-DMSSA), to efficiently reduce the inserted noise during the POCS like iterations, thus can improve the final performance of simultaneous reconstruction and denoising. Application of the MS-DMSSA approach on 3D synthetic and field seismic data demonstrates a better performance compared with the conventional MSSA approach.