Seismic time-frequency analysis via time-varying filtering based empirical mode decomposition method

被引：16

作者：

Chen, Siyuan ^{[1
,4
]}

Cao, Siyuan ^{[1
,4
]}

Sun, Yaoguang ^{[1
,4
]}

Lin, Ying ^{[2
,5
]}

Gao, Jun ^{[3
]}

机构：

[1] China Univ Petr, Coll Geophys, Beijing 102249, Peoples R China

[2] China Univ Petr East China, Sch Geosci, Qingdao 266580, Peoples R China

[3] Sinopec Petr Explorat & Prod Res Inst, Beijing 100083, Peoples R China

[4] China Univ Petr, CNPC Key Lab Geophys Explorat, Beijing 102249, Peoples R China

[5] China Univ Petr East China, Key Lab Deep Oil & Gas, Qingdao, Peoples R China

来源：

JOURNAL OF APPLIED GEOPHYSICS | 2022年 / 204卷

关键词：

Empirical mode decomposition; Time varying filtering; Time-frequency analysis; Noise attenuation; SPECTRAL DECOMPOSITION; ATTENUATION; TRANSFORM;

D O I：

10.1016/j.jappgeo.2022.104731

中图分类号：

P [天文学、地球科学];

学科分类号：

07 ;

摘要：

We proposed a seismic time-frequency analysis method using time-varying filtering based empirical mode decomposition (TVF-EMD). TVF-EMD is a recently-developed signal decomposition method in the field of nonstationary signal processing. The method is suitable for chirp signals, which address the mode mixing problem. TVF-EMD decomposes the non-stationary signal into IMFs with fixed bandwidth and then applies the instantaneous amplitude, frequency, and phase to build the time-frequency spectrum based on the Hilbert transform. Different from empirical mode decomposition (EMD), TVF-EMD uses the time-varying B-spline filter and adaptively calculates the cut-off frequency at each moment for mode decomposition, which is suitable for non-stationary signal processing. Synthetic and field data examples demonstrate comparing with the conventional methods, TVF-EMD has better time-frequency concentration and is more suitable for processing.

引用

页数：12

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