Signal-to-noise ratio enhancement in seismic data via the modified KL transforms

The conventional KL transform is used for removing noises in seismic data processing, but it has three limitations:when the events are horizontal, the conventional KL transform can enhance the events, but when the events are oblique or curving, using the conventional KL transform will destroy the continuity of effective events;when the coherent noises in seismic data have strong energy, using the conventional KL transform can't effectively remove the coherent noises;and because of the large numbers of calculations, it is impossible for us using the conventional KL transform in practice.Aim at these three limitations, we improve the convertional KL transform:using the dip scanning stack KL transform not only can remove noises effectively, but also can keep the continuity of oblique or curving events well;using the new method, which was named space time variety and dip angle KL transform, the strong coherent noises will be removed clear, and plotting out the whole data into some small blocks can reduce the calculations.At last we combine these three betterments, the results show this new method can improve signal to noise ratio in seismic data well.