Journal ArticleDOI
Application of the Variational-Mode Decomposition for Seismic Time–frequency Analysis
TLDR
Application of the VMD on field data demonstrates that instantaneous spectrum after VMD targets the thickness variation in the coal seam more sensitively than the conventional tools and highlights the fine details that might escape unnoticed.Abstract:
Seismic time–frequency analysis methods play an important role in seismic interpretation for its superiority in significantly revealing the frequency content of a seismic signal changes with time variation. Variational-mode decomposition (VMD) is a newly developed methodology for decomposition on adaptive and quasi-orthogonal signal and can decompose a seismic signal into a number of band-limited quasi-orthogonal intrinsic mode functions (IMFs). Each mode is an AM–FM signal with the narrow-band property and nonnegative smoothly varying instantaneous frequencies. Analysis on synthetic and real data shows that this method is more robust to noise and has stronger local decomposition ability than the empirical mode decomposition (EMD)-based methods. Comparing with the short-time Fourier transform (STFT) or wavelet transform (WT), instantaneous spectrum after VMD promises higher spectral and spatial resolution. Application of the VMD on field data demonstrates that instantaneous spectrum after VMD targets the thickness variation in the coal seam more sensitively than the conventional tools and highlights the fine details that might escape unnoticed. The technique is more promising for seismic signal processing and interpretation.read more
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Hybrid wind energy forecasting and analysis system based on divide and conquer scheme: A case study in China
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Denoising of UHF PD signals based on optimised VMD and wavelet transform
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Thermally-induced error compensation of spindle system based on long short term memory neural networks
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References
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Journal ArticleDOI
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