Multi-channel bipolar sparse spectrum inversion method based on Hessian matrix constraint
A sparse spectrum and spectrum inversion technology, applied in the field of oil and gas and geophysical exploration, can solve the problems of inability to reflect the distribution of formation reflection coefficients, lack of spatial coherence of reflection coefficients, and dislocation, etc., to achieve rich geological and reservoir information, high Resolution, the effect of increasing the resolution
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Embodiment 1
[0062] like figure 1 As shown, the multi-channel bipolar sparse spectrum inversion method based on Hessian matrix constraints includes the following steps:
[0063] S1. Input multi-channel seismic data.
[0064] S2. Estimate the seismic wavelet to determine the length of the time window, and use the time window to divide the data:
[0065] First, estimate the dominant frequency f of the wavelet of the multi-channel seismic data s(x,t) m :
[0066]
[0067] Among them, S(x,f) represents the amplitude spectrum of the multi-channel signal s(x,t), and M is the number of seismic traces.
[0068] Take the main frequency as f w The length of the zero-phase rake wavelet is used as the window length of the time window, so that the center sampling point of the time window corresponds to the position of the main peak of the zero-phase rake wavelet.
[0069] After that, set the moving window step as a time sampling interval of the multi-channel seismic data, and use the time windo...
Embodiment 2
[0098] The sand-mud interbed wedge-shaped model seismic forward modeling section was inverted using the multi-channel bipolar sparse spectrum inversion method based on Hessian matrix constraints described in Example 1. The sand-mud interbed wedge-shaped model seismic forward modeling section was as follows: figure 2 As shown, the calculated reflection coefficient profile is as follows image 3 shown.
Embodiment 3
[0100] The Marmousi model seismic forward profile is inverted using the multi-channel bipolar sparse spectrum inversion method based on Hessian matrix constraints described in Example 1. The Marmousi model seismic forward profile is as follows: Figure 5 As shown, the calculated reflection coefficient profile is as follows Image 6 shown.
[0101] Will image 3 , Image 6 The inversion results shown are the same as the conventional spectral inversion results ( Figure 4 , Figure 7 ), it can be seen that: the resolution capability of conventional spectral inversion for thin layers is relatively poor, when the thickness of thin layers is less than 1 / 8 wavelength, it cannot be resolved, and the position of reflection coefficients is displaced and lacks lateral continuity; based on Hessian matrix Constrained multi-channel bipolar sparse spectral inversion can resolve thin layers with a thickness less than 1 / 8 wavelength, and the reflection coefficient has good lateral continu...
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