Mengyao Sun

Alternating traveltime tomography and waveform inversion for near-surface imaging

Near-surface imaging often plays a significant role in producing quality data processing results for the deep subsurface structure in land and shallow marine environments. First-arrival traveltime tomography is a common approach for near-surface imaging due to its high efficiency and simplicity. However, the method faces with issues of missing hidden layers and resolving the structures with low resolutions. On the other hand, waveform inversion should offer better solutions for dealing with these issues but may suffer from the cycle skipping problem. We intend to use the advantages and reduce the disadvantages of the two methods by developing a new strategy of alternately applying traveltime tomography and waveform inversion through iterations. First-arrival traveltime tomography applies a wavefront raytracer and a nonlinear inversion approach. Waveform inversion is a multiscale approach in which a wavelet transform is applied in the data domain to better handle the cycle skipping problem. By alternating the two inversions rather than performing a joint inversion, we reduce the memory requirements and avoid non-physical scaling problems between the two methods. With a synthetic test and real data example, we demonstrate that alternating inversions minimize two separate objective functions at the same time and constrain the near-surface structures fairly well compared with the waveform inversion alone.