Method for fast prediction of shallow water multiples in frequency-wavenumber domain

By converting seismic data to the frequency wavenumber domain and using radial trace transformation and interpolation algorithms combined with wavefield extension operators, the problem of shallow water multiple prediction in traditional methods is solved, achieving efficient and high-precision multiple prediction and suppression, and improving the resolution of marine seismic data.

CN122153415APending Publication Date: 2026-06-05CHINA PETROLEUM & CHEMICAL CORP +1
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
CHINA PETROLEUM & CHEMICAL CORP
Filing Date
2024-12-04
Publication Date
2026-06-05

AI Technical Summary

Technical Problem

Existing multiple suppression methods cannot quickly and accurately predict shallow water multiples, and are difficult to effectively separate from effective signals, which can easily damage the signal and reduce the signal-to-noise ratio of seismic data.

Method used

The time-domain seismic data is converted to the frequency-wavenumber domain, and the tau-p transformation is performed using radial trace transformation and interpolation algorithms. Combined with the convolution of the shallow water wavefield extension operator, the shallow water multiple wave model is predicted, and attenuation and suppression are performed through adaptive subtraction.

Benefits of technology

It achieves efficient and high-precision prediction of shallow water multiples, effectively suppresses multiples in marine seismic data, and at the same time protects the effective signal to the greatest extent, thereby improving the resolution of seismic data.

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Abstract

The application discloses a method for rapidly predicting shallow water multiple waves in a frequency-wavenumber domain, which comprises the following steps: converting time domain seismic data into frequency-wavenumber domain seismic data; performing tau-p transformation on the frequency domain seismic data by using a radial path transformation algorithm and an interpolation algorithm to obtain seismic data in an omega-p domain; and performing convolution on the seismic data in the omega-p domain and a shallow water layer wave field continuation operator containing reflection information of a shallow water layer to obtain predicted shallow water multiple wave model data. The method adopts the idea of combining data driving with model driving, directly performs model continuation on input seismic data, and realizes efficient and high-precision prediction of shallow water multiple waves.
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