Exploration seismic data are heavily manipulated before human interpreters are able to
extract meaningful information regarding subsurface structures. This manipulation adds …

Full-waveform inversion (FWI) promises a high-resolution model of the earth. It is, however,
a highly nonlinear inverse problem; thus, we iteratively update the subsurface model by …

Extracting physical parameters that cannot be directly measured from an observed data set
remains a great challenge in several fields of science and physics. In many of these …

Full waveform inversion has shown its huge potentials in recovering a high‐resolution
subsurface model. However, conventional full waveform inversion usually suffers from cycle …

Full-waveform inversion (FWI) is popularly used to retrieve a high-resolution velocity model
that maximizes the data fitting directly. It is a highly nonlinear optimization problem, and thus …

Cycle skipping is a severe issue in full-waveform inversion. One option to overcome it is to
extend the search space to allow for data comparisons beyond the “point-to-point” …

We have developed a method to obtain a misfit function for robust waveform inversion. In
this method, called adaptive traveltime inversion (ATI), a matching filter that matches …

A full-waveform inversion (FWI) is a highly nonlinear inversion methodology. FWI tends to
converge to a local minimum rather than a global one. We refer to this phenomenon as …

By taking advantage of the information carried by the entire seismic wavefield, Full
Waveform Inversion (FWI) is able to yield higher resolution subsurface velocity models than …

Considering the conventional seismic wavelength and the nature of the Earth's layering,
seismic waves experience, in many parts of the subsurface, considerable anisotropy, and …