Curvelet transform anti-aliasing seismic data reconstruction method based on projection onto convex set algorithm

Abstract

The invention discloses a curvelet transform anti-aliasing seismic data reconstruction method based on a projection onto convex set algorithm. The method is characterized in that aiming at aliasing seismic data with rule lack or aliasing seismic data with large sampling interval, firstly decomposing curvelet transform into an f-k operator and a curvelet splicing operator, starting from an f-k domain origin, obtaining an energy distribution map by employing full-frequency-band information and an angle scanning policy, and picking a boundary peak value of the distribution map, wherein the boundary represents an effective wave energy boundary; selecting a proper threshold, and establishing a corresponding mask function according to the effective wave energy in the boundary peak; and finally introducing the mask function to the conventional projection onto convex set algorithm to obtain a new projection onto convex set algorithm, and in an iteration process, reconstructing the anti-aliasing seismic data by employing a hard threshold operator and an index threshold parameter formula. According to the method, the signal-to-noise ratio and the calculating speed of the reconstructed signalare increased, the weak effective wave signal is protected, and reflecting wave events are more continuous and clear.

Description

technical field [0001] The invention relates to a seismic data reconstruction method with missing rules and large missing intervals, in particular to a curvelet transform anti-aliasing seismic data reconstruction method based on a convex set projection algorithm. technical background [0002] In the process of field data collection, in order to obtain relatively complete and regular seismic data, the field observation system must be designed before data collection. It usually deviates from the original design position, and even some shot receivers cannot collect effective seismic data, which leads to irregular undersampling of seismic data along the spatial direction and spatial aliasing (Trad, 2009; Zhao et al., 2013) . This spatially under-sampled false-frequency seismic data seriously affects subsequent processing methods, such as multiple wave suppression, velocity analysis, and wave equation migration. In order to solve this problem, the most direct and effective meth...

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Problems solved by technology

In the data reconstruction process, the convex set projection algorithm is widely used, but according to the principle of the convex set projection algorithm, the algorithm does not have the function of anti-aliasing, and cannot reconstruct the aliasing data with missing rules. For this reason, the present invention Using the curvelet transform method, using the full frequency band data to establish the mask function, a curvelet transform anti-aliasing seismic data reconstruction method based on the convex set projection algorithm is proposed, which can effectively reconstruct the method while ensuring the reconstruction accuracy and efficiency Serious false frequency seismic data with missing rules

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