Abstract
The frequency spectrum of irregular interference noise has broad bandwidth and poor coherence.But in the same prospecting area, the dominant frequency and bandwidth of effective signals are nearly the same (especially for post-stack section); that is to say, the frequency spectra of effective signals in seismic traces show a high degree of trace-to-trace correlation. Based on this conclusion, we present a novel denoising technique, which works by SVD filtering in the frequency domain. First, the input seismic data are transformed to the frequency domain via the Fourier transform. Then, the frequency spectra are decomposed into eigenimages by means of SVD. We perform the eigenimage filtering of the frequency spectra by selecting singular values to be used in the reconstruction, suppressing the random noise. Compared with the traditional band-pass filtering, the presented method is capable of attenuating the interference noise components within the range of frequency pass band and protects effective signals in high frequency. Tests on both synthetic and field seismic data show that our method can remove random noise and does no damage to effective signal. By comparison with the median filtering and the curvelet domain filtering, we concluded that the presented denoising method performs better in removing background noise and protecting reflection events.
Highlights
Reflected seismic signals describing the underlying geological structure are usually contaminated by random noise
In the research presented in this paper, we propose a novel denoising technique which works by Singular value decomposition (SVD) filtering in frequency domain
In the same area, the dominant frequency and bandwidth of effective signals in seismic traces are nearly the same, i.e., the frequency spectra of effective signals show a high degree of trace-to-trace correlation. Based on this point of view, firstly, the input seismic data are transformed to the frequency domain via the Fourier transform
Summary
Reflected seismic signals describing the underlying geological structure are usually contaminated by random noise. Keywords Fourier transform · Eigenimage filtering · Random noise · Signal-to-noise ratio · Seismic data In the research presented in this paper, we propose a novel denoising technique which works by SVD filtering in frequency domain. In terms of selected singular values corresponding to the target signal, eigenimages are extracted to reconstruct the filtered spectra.
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