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.