Seismic wave full waveform inversion method based on least square gradient update speed model

Abstract

The present invention relates to a seismic wave full waveform inversion method based on a least square gradient update speed model, comprising the following steps: 1) obtaining a sound wave equation of a seismic wave field in time domain; 2) constructing an initial speed model, setting a speed model update iteration number N and an allowed minimum error value epsilon; 3) constructing observation wave field data and calculating a wave field error vector of the wave field data; 4) constructing an object function; 5) calculating the object function to obtain a standard equation of seismic wave full waveform inversion; 6) introducing a speed model update gradient direction g<k> and an update amount step length alpha; 7) solving the speed model update gradient direction g<k> by using a least square method; 8) performing interpolation calculation for the update amount step length alpha; and 9) updating the speed model, wherein m<k>=m<k-1>+alpha*g<k>; when |alpha*g<k>| < epsilon or the update number of the speed model reaches the speed model update iteration number N, ending the update of the speed model; otherwise, entering into the step 3). The seismic wave full waveform inversion method of the present invention can quickly achieve update of the speed model, and can be widely applied in seismic wave full waveform inversion.

Description

technical field [0001] The invention relates to a seismic wave full waveform inversion method, in particular to a seismic wave full waveform inversion method based on a least square gradient update velocity model. Background technique [0002] There are many seismic wavefield inversion methods, such as phase inversion imaging, amplitude inversion imaging and full waveform inversion imaging. Phase inversion and amplitude inversion use the kinematic information of the wave field, and the inversion velocity distribution is a smooth estimation value, which is the low-frequency component of the true velocity model and reflects the large-scale velocity structure. The full waveform inversion based on the wave equation theory comprehensively utilizes the complete wavefield information such as amplitude, travel time and phase in the seismic records. The quadratic functional of the recorded difference and additional geological constraints are used to establish the optimization object...

AI Technical Summary

Problems solved by technology

However, inversion uses a lot of low-frequency information to update the background velocity, while migration uses high-frequency information to delineate the more accurate boundaries of subsurface structures. Since the targets of inversion and migration are in different frequency bands, in actual processing , due to noise and model artifacts, high fidelity is difficult to achieve, and in the conventional full waveform inversion process, in each nonlinear iteration process of full waveform inversion, only one reverse time migration imaging result is used as the velocity The direction of the model update gradient, which will easily lead to insufficient update amount of update gradient calculation, and the convergence speed is slow

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