Time Domain Full Waveform Inversion Based on Gradient Preconditioning with an Angle-Dependent Weighting Factor

There are lots of low wavenumber noises in the gradients of time domain full waveform inversion(FWI), which can seriously reduce the accuracy and convergence speed of FWI. Thus, we introduce an angle-dependent weighting factor to precondition the gradients so as to suppress the low wavenumber noises when the multi-scale FWI is implemented in the high frequency. Model experiments show that the FWI based on the gradient preconditioning with an angle-dependent weighting factor has faster convergence speed and higher inversion accuracy than the conventional FWI. The tests on real marine seismic data show that this method can adapt to the FWI of field data, and provide high-precision velocity models for the actual data processing.