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张懿洁

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Fluvial channel characterization using the improved empirical wavelet transform

发布时间:2025-04-30  点击次数:

发布时间:2025-04-30

论文名称:Fluvial channel characterization using the improved empirical wavelet transform

发表刊物:SEG Technical Program Expanded Abstracts 2019

摘要:The empirical wavelet transform (EWT) builds an adaptive filter bank and decomposes an analyzed signal into several intrinsic mode functions (IMFs). Although some applications have certified the effectiveness of the EWT, the EWT becomes invalid when analyzing non-stationary signals (e.g. seismic signals). In this paper, we propose an improved empirical wavelet transform (IEWT) to decompose a seismic signal into several IMFs and describe its frequency features. After computing the Fourier spectrum of the analyzed seismic signal, we first implement the scale-space representation (SSR) to the Fourier spectrum. Then, we obtain an adaptive spectrum segmentation using detected boundaries based on the SSR. Afterward, the proposed algorithm obtains accurate and stable IMFs in decomposing a nonstationary seismic signal. To demonstrate the effectiveness of the proposed IEWT, we apply it to synthetic seismogram and field data.

合写作者:Naihao Liu, Qian Wang, Hui Li, Yijie Zhang, and Jinghuai Gao

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发表时间:2019-09-18

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