Full Waveform Inversion Using Free-Surface Related Multiples as Natural Blended Sources

To improve the computational speed of conventional full waveform inversion (FWI), we propose a new FWI method which uses free-surface related multiples as natural blended sources and name it as NBFWI. The proposed method contains four key steps: 1. at selected source locations, forward propagate synthetic wavelet to generate calculated shot records containing both primaries and free-surface related multiples; 2. Compared with recorded field data to obtain waveform residuals; 3. backward propagate waveform residuals and forward propagate recorded field data to produce gradient; 4. use steep descent method or other optimization methods for velocity updating. Compared with other blended sources methods, the NBFWI method has no need of implementing phase encoding algorithms and the free-surface related multiples act as natural blended sources. A Marmousi velocity model is used for numerical tests. The numerical results show how accurate, efficient and stable the proposed approach is when using different number of shot gathers for inversion. Because of the utilization of wide coverage characteristics of free-surface related multiples, the inversion procedure has good convergence even using very few shots. The proposed approach is easy to implement and maybe significant for both fast velocity model building and inversion of sparse acquisition data.