Peak noise suppression method of variable-window weighted seismic data

Abstract

The invention relates to a peak noise suppression method of variable-window weighted seismic data and aims at solving various problems that peak noise has characteristics of high energy, occurrence time randomness and wide frequency band, a noise source is complicated and variable to cause that a plurality of peak noises have different continuous time and frequency band widths, the peak noise cannot be favorably suppressed by a fixed-window peak noise suppression method and the applicability is poor. Through experiment, the method has a favorable suppression effect on seismic data disturbed bystrong peak noise with different continuous time, the peak noise is effectively suppressed, and the characteristic of a signal can be maintained according to a detected peak noise changing window length autonomous estimation weight. Compared with an existing mid-value substitution method, the peak noise suppression method has the advantages that the resolution of identifying the peak noise is higher, and the signal energy is fully maintained; and meanwhile, the peak noise suppression method is applicable to different environmental situations, the characteristic of the peak noise is analyzed in real time, the peak noise is suppressed, and the quality of acquired data is effectively ensured.

Description

Technical field: [0001] The invention relates to a seismic data processing method, in particular to a duration-based variable window weighted seismic data spike noise suppression method, which is especially suitable for denoising processing of seismic signals seriously interfered by spike noise. Background technique: [0002] The noise environment in the process of seismic exploration data acquisition is very complex. In addition to random noise and power frequency interference, the collected seismic data also has significant spike noise. As the signal-to-noise ratio of the data decreases, the frequency of spike noise increases. The quality dropped drastically. The peak noise is usually similar to the signal amplitude or significantly higher than the signal and other types of noise in terms of signal amplitude. Therefore, the existence of a large number of spike noise makes it difficult to detect and identify effective signals. [0003] At present, the commonly used suppres...

AI Technical Summary

Problems solved by technology

Methods such as zero substitution method, mean value substitution method and nonlinear energy usually select a fixed window length to calculate the median value. For complex environmental noise, the duration of spike noise is variable. When the duration of spike noise is long and the signal frequency is high, substitute The value does not reflect the true characteristics of the signal; the zero substitution method sacrifices the signal energy at the time of the spike noise, and when the spike noise occurs more frequently, the signal is greatly lost and cannot be recovered

The statistical superposition method needs to collect data multiple times, which increases the cost of collection, and this method cannot be applied to the data that has been collected

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