Random noise suppression method and apparatus for seismic data

Abstract

The invention relates to the seismic exploration field, especially to a random noise suppression method and apparatus for seismic data. The method comprises: complementary ensemble empirical mode decomposition (CEEMD) is carried out on seismic data to obtain an intrinsic mode function (IMF) component sequence, and according to an interrelation between seismic data and IMF components, IMF components including random noises and IMF components not including random noises are determined; on the basis of differences of the random noises included by the IMF components including random noises, different threshold values are selected for the IMF components including random noises to carry out optimal curvelet iteration threshold de-noising processing, thereby obtaining the processed IMF components; and then seismic data after noise removing are obtained by reconstruction. According to the method provided by the embodiment of the application, on the basis of combination of the CEEMD and the optimal curvelet iteration threshold method, defects of effective signal loss due to an EMD method and de-noising method and single threshold selection because of a curvelet threshold de-noising method can be overcome. The effective signal can be kept well while random noises are suppressed, so that the signal to noise ratio of seismic data is improved.

Description

technical field [0001] The invention relates to the field of seismic exploration, in particular to a random noise suppression method and device for seismic data. Background technique [0002] According to the characteristics of the noise on the seismic section, the noise can be divided into regular noise and irregular noise. Regular noise mainly refers to noise with a certain main frequency and a certain apparent velocity, such as surface waves, alternating current interference, sound waves, shallow refraction, etc. Irregular noise, that is, random noise, mainly refers to waves with no fixed frequency and fixed propagation direction, forming a chaotic background in seismic data. Random noise is characterized by a wide frequency and no apparent velocity in seismic records, so it is difficult to suppress it by using the difference in frequency spectrum or the difference in propagation direction between random noise and effective wave. Due to the complexity of surface conditi...

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Problems solved by technology

The Fourier transform filtering method needs to assume that the signal is stationary, and it is difficult to characterize the local characteristics of the signal. When the signal is non-stationary, this method is difficult to achieve the desired effect; the independent component analysis method requires that the seismic signal and random noise are statistically independent, However, this method assumes that the data trace is multiple observations of the same trace, and the actual seismic trace data does not satisfy this assumption, indicating a very rough approximation, so its ability to suppress random noise is not ideal

The two-dimensional wavelet transform method is widely used in seismic data processing, but because its basis function is isotropic, the local maximum value of the transform coefficient can only reflect that the position where the wavelet coefficient appears is "over " edge, but cannot express the information "along" the edge, so the two-dimensional wavelet transform method is not ideal for image edge data processing

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