C-10 EFFICIENT COHERENT NOISE FILTERING: AN APPLICATION OF SHIFT-INVARIANT WAVELET DENOISING

Coherent noise or surface waves filtering represents one of the most complex issues in land seismic data processing. Wavelet based filtering has recently begun to challenge the popular and robust frequencywavenumber ( - - ) filter. Wavelet filters provide fine time-scale representations and non linear filtering capabilities that yield in some instances better results on dispersive coherence noise. We propose in this work an improvement over the classical discrete wavelets filtering via the use of shift-invariant wavelets. Though relatively computationally expensive, their theoretical framework enables a closer approximation to the continuous wavelets, which results in finer filtering, less subject to aliasing and to wavelet ringing artifacts. Results are demonstrated on real seismic data sets. Improvements on ground-roll filtering show shift-invariant wavelets to be promising denoising techniques.