Ground-roll noise attenuation using a simple and effective approach based on local bandlimited orthogonalization |
The problem of bandpass filtering for removing ground-roll noise is the difficulty of choosing an optimal LBF, because of the frequency-overlap problem of ground-roll noise and primary reflections. Figure 3 shows a demonstration of the frequency-overlap problem. When Hz, all the ground-roll noise has been removed, and the denoised section (Figure 3a) does not contain any ground-roll noise. However, the noise section (Figure 3b) contains a lot of coherent signals: both direct waves and primary reflections. When Hz, the noise section (Figure 3d) does not contains any coherent reflection or direct waves, however, the denoised section (Figure 3c) still contains a large amount of ground-roll noise.
One of the most commonly used approaches to solve the frequency-overlap problem is to use matched filtering. The removed ground-roll noise after a common bandpass filtering is used as an initial guess for the ground-roll noise. A least squares (LS) based matching filter is then calculated to match the initial ground-roll noise to the raw seismic data based on the least-energy assumption. The matched ground-roll noise is then subtracted from the raw seismic data to obtain the ground-roll noise attenuated profile. However, this adaptive subtraction method depends highly on the initial prediction of the ground-roll noise. Besides, in the case of highly non-stationary primary reflections and ground-roll noise, a conventional stationary matched filtering is not physically reasonable, and thus will not likely provide a satisfactory performance. In the next sections, we will introduce a novel approach for attenuating ground-roll noise based on bandpass filtering, which can remove more ground-roll noise and preserve more useful primary reflections.
Ground-roll noise attenuation using a simple and effective approach based on local bandlimited orthogonalization |