High-precision inverse Q filtering seismic data processing method

Abstract

The invention provides a high-precision inverse Q filtering seismic data processing method and belongs to the field of seismic signal processing. The method comprises the following steps: (1) extracting quality factor Q value from the frequency domain of original seismic trace signals u0 (tau), (2) converting seismic signals u0 (Tau) into a time-frequency spectrum (img file='DDA00002263127300011.TIF' wi='177' he='67' / ) through Gabor forward transformation, wherein tau is travel-time, and omega is angular frequency, (3) conducting inverse Q filtering on the time-frequency spectrum (img file='DDA00002263127300012.TIF' wi='150' he='67' / ) so as to obtain a new time-frequency spectrum U (tau, omega), (4) through the Gabor forward transformation, converting the U (tau, omega) into time domain seismic tracel signal u (tau) after inverse Q filtering compensation. Through the method, full-frequency Q value stable compensation can be realized, and seismic amplitude information can be recovered as far as possible. The method is an effective seismic signal processing method in the amplitude compensation aspect.

Description

technical field [0001] The invention belongs to the field of seismic signal processing, and in particular relates to a high-precision inverse Q filter seismic data processing method. Background technique [0002] The main geological targets of oil exploration today have changed from simple structural oil and gas reservoirs to subtle and complex structural oil and gas reservoirs, which put forward higher requirements for the accuracy of exploration. However, the propagation of seismic waves in the subsurface will produce absorption and attenuation phenomenon, and its amplitude will decrease rapidly with the increase of propagation time path, thus reducing the signal-to-noise ratio and resolution of seismic data. In order to solve this phenomenon, an inverse Q filter is proposed, which can restore high-frequency information, improve the energy of weak reflection waves and the signal-to-noise ratio and resolution of seismic data. [0003] For the inverse Q filter algorithm, do...

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Problems solved by technology

[0032] However, it can be seen that when the value of β(τ, ω) is less than 0.03, the mathematical approximation calculation error of formula (9) is relatively large, for example, when the quality factor Q value is small or the seismic wave propagation time is large, it will lead to a stable global algorithm Inverse Q filter amplitude recovery effect is not ideal

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