Method for improving seismic data resolution

Abstract

The invention discloses a method for improving seismic data resolution. The method comprises the specific steps of: applying continuous wavelet transform (CWT) time series analysis to original seismic data; calculating harmonic information W<~>( tau, s) of wavelets at various scales through harmonic frequency analysis by utilizing a multiresolution feature of a continuous wavelet domain; transforming the harmonic information back into a time domain through inverse transformation; adding obtained time threshold information into the original seismic data, and expanding frequency width of the seismic data effectively. The method disclosed by the invention breaks through the limitation of the traditional convolution model in the method principle, does not need to estimate seismic wavelets anymore, does not need to assume that a stratum reflection coefficient is sparse, extracts harmonic components by utilizing dominant frequency band information, ensures that a frequency expanding result has a high signal-to-noise ratio, is implemented by adopting an FFT algorithm specifically, is high in calculation efficiency, and can expand the low frequency and high frequency simultaneously.

Description

technical field [0001] The invention relates to the technical field of harmonic frequency, in particular to a method for improving the resolution of seismic data. Background technique [0002] In seismic data processing, signal-to-noise ratio and resolution are two important indicators for evaluating the quality of seismic data. Seismic data with high signal-to-noise ratio and high resolution can be used for effective inversion and geological interpretation, laying a solid foundation for fine reservoir description. Therefore, how to effectively improve the resolution and signal-to-noise ratio of seismic data is a key issue in seismic data processing. [0003] Combining the multi-resolution characteristics of seismic signals in the continuous wavelet domain, we expand the effective bandwidth of seismic data according to the idea of ​​harmonic frequency analysis, which can greatly improve the resolution of seismic data, which is difficult to achieve by other methods. [0004...

AI Technical Summary

Problems solved by technology

[0016] 2. The formation reflection coefficient must satisfy the sparse assumption;

[0017] 3. The original seismic record must have a high signal-to-noise ratio, otherwise the result of frequency expansion will generate more noise;

[0018] 4. The computational complexity of solving the compressed sensing problem is relatively large, and the efficiency of the method is low

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