Reflection full waveform inversion has become an effective tool to generate low-wavenumber deep model update using reflected energy and to improve seismic imaging, especially in the subsalt area. However it is still a challenging inverse problem that suffers from local minima issues. To tackle this problem, we propose a new weighted traveltime based objective function with the correction of the kinematic errors between the synthetic and real data, instead of simply minimizing the data residual for least squares objective function. Therefore it helps avoid cycle skipping issues to overcome some of the problems with local minima and relaxes the requirement for successful inversion. Additionally, we propose a preconditioned optimization scheme to mitigate the artifacts from the kernel of reflection full waveform inversion and improve convergence rate with better results. We compare synthetic examples to demonstrate the benefits. The field example shows successful low wavenumber update from reflections with improved subsalt images.


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