Frequency domain three-dimensional irregular earthquake data reconstruction method

Abstract

The invention brings forward a frequency domain three-dimensional irregular earthquake data reconstruction method. The method is characterized in that first of all, three-dimensional earthquake data in a time domain is converted to a frequency domain by use of Fourier transform, and then, a projection onto convex set (POCS) algorithm is employed and curvelet transform capable of describing localized features of the earthquake data is introduced; and in an iteration process, a new threshold parameter attenuating according to an index rule is brought forward, and each frequency slice is individually reconstructed by use of a soft threshold operator, such that the iteration frequency is reduced, the reconstruction precision is improved, and the purpose of reconstructing the three-dimensional earthquake data is realized. According to the invention, the new threshold parameter attenuating according to the index rule is brought forward and each frequency slice is reconstructed in individually by use of the soft threshold operator, such that the disadvantage of quite slow convergence speed of a conventional threshold parameter is overcome, the calculation complexity of an algorithm is reduced, the calculation efficiency is substantially improved, and the operation time is reduced.

Description

Technical field [0001] The invention relates to a method for reconstruction of missing-track seismic data, in particular to a method for reconstruction of three-dimensional irregular seismic data in the frequency domain. technical background [0002] In the field data acquisition process, due to the limitations of acquisition equipment, project cost and topographical conditions, the seismic data is usually sampled irregularly in the spatial direction below the Nyquist sampling theorem, which results in irregular and irregular sampling of the seismic data collected. Incomplete, there is spatial aliasing, and it is difficult to meet the requirements of subsequent processing, such as velocity analysis, free surface multiple elimination, offset homing, etc. In this case, it is necessary to develop a better seismic data reconstruction method to reconstruct the Missing seismic traces can obtain seismic data that meets the processing requirements, and this method can also guide field da...

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Problems solved by technology

), however, this method reconstructs in the time domain and only uses hard threshold parameters for processing. When the reconstruction data contains both high and low energy amplitude events, the POCS algorithm is below the threshold parameter in the previous few iterations. The event coefficient of the event is filtered out, so these methods have limited effect on reconstructing the low-amplitude significant wave event, and cannot fully restore the low-energy event of the seismic signal and improve the signal-to-noise ratio of the local anomaly area, and the number of iterations is large, and the reconstruction Low efficiency restricts the further application of this method

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