摘要：Full waveform inversion (FWI) is a strongly nonlinear optimization problem, which suffers from cycle skipping when the initial velocity model is not good enough or the seismic data lack low frequencies. Traveltime tomography is often used to invert the low‐wave number components of a velocity model, but traveltime inversion results show a low‐resolution model. To bridge the inversion wave number gap between the traveltime tomography and the FWI, a wave equation‐based local travetime inversion is proposed. In this case, the cross‐correlation algorithm is applied to calculate the traveltime differences between the localized synthetic and observed data. To mitigate traveltime crosstalk noise caused by multiple seismic events, a sliding Gaussian window is applied to transform the seismic data into local domain. In this way, the traveltime information of different seismic events can be simultaneously used to improve the inversion results. The numerical examples show that the combination of Local Traveltime Inversion (LTI) and FWI successfully mitigate the cycle skipping and produce satisfactory inversion results, even if the seismic data lack low frequencies and the initial velocity model is far from the true one. Plain Language Abstract The high resolution of the velocity inversion is important for oil and gas exploration. However, the full waveform inversion results may be trapped into the local minima. This paper introduces a wave equation‐based local traveltime inversion to provide a good initial model for the FWI method. The numerical results verify the correctness of our idea.
