A Curvelet Transform Anti-aliasing Seismic Data Reconstruction Method Based on Convex Set Projection Algorithm

Abstract

The invention discloses a curvelet transform anti-aliasing seismic data reconstruction method based on a convex set projection algorithm. The transformation is decomposed into f-k operator and curvelet splicing operator, starting from the origin of f-k domain, using the information of the whole frequency band, adopting the angle scanning strategy to obtain the energy distribution map and picking the boundary peak in the distribution map, the boundary represents the effective Wave energy boundary, and then select the appropriate threshold, establish the corresponding mask function according to the effective wave energy in the boundary peak, and finally introduce the mask function into the traditional convex set projection algorithm to obtain a new convex set projection algorithm; in the iterative process, The exponential threshold parameter formula is used to reconstruct the seismic data without aliasing by using the hard threshold operator. The invention improves the signal-to-noise ratio and calculation speed of the reconstructed signal, protects the weak effective wave signal, and makes the event axis of the reflected wave 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. [0002] technical background [0003] 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 effect...

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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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