Earthquake Energy Compensation Method Based on Complementary Ensemble Empirical Mode Decomposition

Abstract

The invention discloses an earthquake energy compensation method based on complementary set empirical mode decomposition, wherein the method belongs to the field of oil-gas geophysical exploration. The method comprises the following steps of (1), adding a positive white noise and a negative white noise into original signal data; (2), respectively performing empirical mode decomposition on a positive white noise hybrid signal and a negative white noise hybrid signal; (3), calculating a mean value of a positive white noise hybrid signal inherent mode function component set and a negative white noise hybrid signal inherent mode function component set; (4), performing energy compensation on each mean value of the inherent mode function components; and (5), superposing all mean values of the inherent mode function components after energy compensation, thereby obtaining a seismic cross-section after energy compensation. According to the earthquake energy compensation method based on complementary set empirical mode decomposition, a frequency dividing characteristic in complementary set empirical mode decomposition is utilized, and energy compensation is performed on the inherent mode function components with different frequency components according to an automatic gain control method.

Description

technical field [0001] The invention relates to the field of oil and gas geophysical prospecting engineering, in particular to a seismic energy compensation method based on complementary set empirical mode decomposition. Background technique [0002] The study of the basic properties of non-stationary and nonlinear signals is a key issue in signal analysis, and seismic signals are often non-stationary and nonlinear. Fourier transform is a milestone in signal analysis theory and has been widely used in various fields. However, because it can only obtain the frequency domain information of the signal, and the frequency domain information is only global information, it is impossible to obtain the signal information. Time domain information, so the non-stationary signal whose signal changes with time cannot be processed by Fourier transform. [0003] Compared with Fourier transform, other signal analysis methods such as wavelet transform have been greatly improved in some aspec...

AI Technical Summary

Problems solved by technology

Although empirical mode decomposition has great advantages in frequency division processing of seismic signals, due to its own spectrum aliasing problem, it will lead to inaccurate signal decomposition, making empirical mode decomposition lose its original physical meaning

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