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access icon free Seismic trace noise reduction by wavelets and double threshold estimation

© The Institution of Engineering and Technology
Received 13/02/2017, Accepted 13/07/2017, Revised 10/06/2017, Published 18/07/2017

In this study, the authors propose the seismic trace noise reduction by wavelets and double threshold estimation method (STNRW), that is based on the discrete wavelet transform, estimates two thresholds instead of the one threshold estimation of the traditional methods. The authors verify the robustness of the method proving that the probability of classification error for a noisy wavelet coefficient decreases, as the length of the signal increases. The authors perform Monte Carlo simulations considering eight seismic traces obtained from astsa R package with different signal-noise-to-ratio (SNR) values in order to compare the performance of the new method with three denoising methods well-known in the literature. The results show that the STNRW method is efficient.

Inspec keywords: error statistics; Monte Carlo methods; signal denoising; geophysical signal processing; discrete wavelet transforms; signal classification; seismic waves

Other keywords: astsa R package; Monte Carlo simulations; classification error probability; double threshold estimation; SNR values; signal-noise-to-ratio; STNRW method; seismic trace noise reduction by wavelets; noisy wavelet coefficient; discrete wavelet transform

Subjects: Digital signal processing; Monte Carlo methods; Seismic waves; Instrumentation and techniques for geophysical, hydrospheric and lower atmosphere research; Signal processing and detection; Geophysics computing; Integral transforms; Geophysical techniques and equipment; Monte Carlo methods; Integral transforms

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