A Fuzzy Time-varying Time-frequency Peak Filtering For Random Seismic Noise Elimination

摘要

The time-frequency peak filtering (TFPF) is the effective method for removing the strong random noise in seismic data. For preserving the subtle structures of the seismic signal in attenuating random noise, we present the fuzzy time-frequency peak filtering (FTFPF) algorithm to further improve the resolution of the results of TFPF, using multiple time-windowing lengths for TFPF. The new method uses a fuzzy determination threshold to identify the noise segment and signal segment in seismic data by using the filtered data of TFPF with long windowing length. The multi-level windowing lengths then are set for FTFPF according to the noise intensity in noise segments and frequency characteristics of signal in signal segments. The longer windowing length is used for noisy segments to remove random noise effectively, and the shorter windowing lengths are used in signal segments to preserve the details of the signal. The FTFPF is applied to synthetic records and common-shot point record, the model analysis indicates that the fuzzy discrimination can identify the signal and noise correctly. The filtered result by FTFPF has better ability to removing noise and preserving signal than TFPF. We have had very good result from common-shot-point record. Consequently, the FTFPF can preserve the local characteristics of signal as well as the effective suppression of random noise.