Full-Waveform Inversion (FWI) is method to get high-resolution of subsurface properties by minimizing the difference between observed and modeled seismic waveforms. Given an initial guess of the subsurface parameters (a model), the data are predicted by solving a wave-equation. The model is then updated in order to reduce the misfit between the observed and predicted data. This is repeated in an iterative fashion until the data-misfit is sufficiently small.
Tomography is one approach to get subsurface velocity, but because it only used travel-time kinematic of seismic data it can only reconstruct the smooth varying properties of the medium. FWI in the other hand use all information in seismic data (amplitude, phase, travel-time) so it can reconstruct properties of subsurface with greater detail.
The highly detailed models of subsurface properties that provided by FWI can be used to resolve complex geological features, as well as aid in identifying potential geohazards. These models can also be input directly to pore pressure prediction flows, time-lapse monitoring and reservoir characterization analysis. Seismic imaging using these highly accurate models will result in increasing confidence of interpretation with respect to reservoir delineation and subsequent well planning.