Seismic signal time-frequency decomposition method based on short-time fractional Fourier transform

Abstract

The invention discloses a seismic signal time-frequency decomposition method based on short-time fractional Fourier transform. A Gaussian window function is selected; high frequency resolution is obtained by adjusting the window width in a self-adapting way; through the characteristic of fractional kernel function angle rotation, the best energy accumulation of the seismic signal is obtained at the optimal rotation angle and the cross term is eliminated; the higher frequency resolution and more accurate frequency location are more conductive to recognizing specific geologic structure, so that the method solves the defects of the existing seismic signal time-frequency decomposition method. The method has the positive effects of overcoming the defects of traditional algorithm such as short-time Fourier and Wigner-Ville distribution and the like and having great significance on seismic signal spectral analysis.

Description

technical field [0001] The invention relates to a seismic signal time-frequency decomposition method based on Short Time Fractional Fourier Transform (STFrFT). Background technique [0002] In seismic exploration, when seismic waves propagate in the underground medium, their propagation path, vibration intensity and waveform will undergo complex changes with the elastic properties and geometric shapes of the medium they pass through. Therefore, the ground will receive signal components such as p-waves, s-waves, large-amplitude divergent surface waves, and various noises that propagate through different paths. They not only have different arrival times, but also have different kinematics and dynamics characteristics. Multiple reflections, refractions and transmissions, and the absorption and attenuation of different frequency components by the subsurface medium are also different. Therefore, the seismic signal is a typical non-stationary signal, and its spectral components a...

AI Technical Summary

Problems solved by technology

[0027] As mentioned above: the Wigner-Willi distribution has good energy aggregation for single-component signals, but for multi-component signals, due to its inherent bilinear nature, this time-frequency decomposition has serious cross terms, It is unfavorable for the detection of some weaker useful components in seismic signals. Short-Time Fourier Transform can avoid the occurrence of cross terms, but the effect of decomposing signal spectrum is not good under the condition of low signal-to-noise ratio seismic signals. ideal

Images