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Estimation of an accurate macro velocity model plays an important role in seismic imaging and model parameter inversion.Full waveform inversion(FWI) is the classical data-domain inversion method.However,the misfit function of FWI is highly nonlinear,and the local optimization cannot prevent convergence of the misfit function toward local minima.To converge to the global minimum,FWI needs a good initial model or reliable low frequency component and long offset data.In this article,we present a wave-equation-based reflection traveltime tomography(WERTT) method,which can provide a good background model(initial model) for FWI and(least-square) pre-stack depth migration(LS-PSDM).First,the velocity model is decomposed into a low-wavenumber component(background velocity) and a high-wavenumber component(reflectivity).Second,the primary reflection wave is predicted by wave-equation demigration,and the reflection traveltime is calculated by an automatic picking method.Finally,the misfit function of the l2-norm of the reflection traveltime residuals is minimized by a gradient-based method.Numerical tests show that the proposed method can invert a good background model,which can be used as an initial model for LS-PSDM or FWI.
Estimation of an accurate macro velocity model plays an important role in seismic imaging and model parameter inversion. Full waveform inversion (FWI) is the classical data-domain inversion method. However, the misfit function of FWI is highly nonlinear, and the local optimization can not prevent convergence of the misfit function toward local minima. To converge to the global minimum, FWI needs a good initial model or reliable low frequency component and long offset data. In this article, we present a wave-equation-based reflection traveltime tomography (WERTT ) method, which can provide a good background model (initial model) for FWI and (least-square) pre-stack depth migration (LS-PSDM) .First, the velocity model is decomposed into a low-wavenumber component (background velocity) and a high-wavenumber component (reflectivity) .Second, the primary reflection wave is predicted by wave-equation demigration, and the reflection traveltime is calculated by an automatic picking method .Finally, the misfit function of the l2-norm of the reflection traveltime residuals is minimized by a gradient-based method. Numerical tests show that the proposed method can invert a good background model, which can be used as an initial model for LS-PSDM or FWI.