Multicomponent microseismic data denoising by 3D shearlet transform
Multicomponent microseismic data denoising by 3D shearlet transform
复制标题
通过 3D 剪切波变换进行多分量微震数据去噪
DOI：
10.1190/geo2017-0788.1
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发表时间：
2018-05
期刊：
影响因子：
3.3
通讯作者：
Mirko van der Baan
中科院分区：
文献类型：
--
作者：
张超;Mirko van der Baan
The low-magnitude microseismic signals generated by fracture initiation are generally buried in strong background noise, which complicates their interpretation. Thus, noise suppression is a significant step. We propose an effective multicomponent, multidimensional microseismic-data denoising method by conducting a simplified polarization analysis in the 3D shearlet transform domain. The 3D shearlet transform is very competitive in dealing with multidimensional data as it captures details of signals at different scales and orientations, which benefits signal and noise separation. We propose a novel processing strategy based on a signal- detection operator which can effectively identify signal coefficients in the shearlet domain by taking the correlation and energy distribution of three-component microseismic signals into account. We perform tests on synthetic and real datasets demonstrate that the proposed method can effectively remove random noise and preserve weak signals.
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影响因子：
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DOI：
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发表时间：
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期刊：
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影响因子：
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3.3
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