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Ground‐roll suppression using the wavelet transform

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Low‐frequency, high‐amplitude ground roll is an old problem in land‐based seismic field records. Current processing techniques aimed at ground‐roll suppression, such as frequency filtering, f-k filtering, and f-k filtering with time‐offset windowing, use the Fourier transform, a technique that assumes that the basic seismic signal is stationary. A new alternative to the Fourier transform is the wavelet transform, which decomposes a function using basis functions that, unlike the Fourier transform, have finite extent in both frequency and time. Application of a filter based on the wavelet transform to land seismic shot records suppresses ground roll in a time‐frequency sense; unlike the Fourier filter, this filter does not assume that the signal is stationary. The wavelet transform technique also allows more effective time‐frequency analysis and filtering than current processing techniques and can be implemented using an algorithm as computationally efficient as the fast Fourier transform. This new filtering technique leads to the improvement of shot records and considerably improves the final stack quality.
Society of Exploration Geophysicists
Title: Ground‐roll suppression using the wavelet transform
Description:
Low‐frequency, high‐amplitude ground roll is an old problem in land‐based seismic field records.
Current processing techniques aimed at ground‐roll suppression, such as frequency filtering, f-k filtering, and f-k filtering with time‐offset windowing, use the Fourier transform, a technique that assumes that the basic seismic signal is stationary.
A new alternative to the Fourier transform is the wavelet transform, which decomposes a function using basis functions that, unlike the Fourier transform, have finite extent in both frequency and time.
Application of a filter based on the wavelet transform to land seismic shot records suppresses ground roll in a time‐frequency sense; unlike the Fourier filter, this filter does not assume that the signal is stationary.
The wavelet transform technique also allows more effective time‐frequency analysis and filtering than current processing techniques and can be implemented using an algorithm as computationally efficient as the fast Fourier transform.
This new filtering technique leads to the improvement of shot records and considerably improves the final stack quality.

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