Full Waveform Inversion (FWI)

High Frequency FWI utilises the entire seismic wavefield to generate refined, high-resolution velocity models for imaging and characterisation.

At a high level, what FWI tries to do is actually quite simple. It iteratively updates an initial model by forward modelling synthetics and comparing them to field data. 

Advances in supercomputing make wave equation-based inversions like Reverse Time Migration and Full Waveform Inversion a lot more practical. As the name suggests, Full Waveform Inversion, or FWI, inverts for a high-resolution earth model (typically velocity), using the entire seismic wavefield. Just as the physics of wave propagation is non-linear, FWI is a highly non-linear parameter estimation problem.

In order to generate synthetics, we have to reproduce the seismic experiment that we carried out in the field. This requires knowledge of the source wavelet, the acquisition geometry, and the physics of 3D wave propagation.

The objective function is then straight forward. We want to optimise our earth model parameters, such as the P-wave velocity, to minimise the difference between the synthetics and the field data. Our FWI implementation can be used in 2D or 3D and can handle isotropy, VTI or TTI.

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Smooth starting velocity model prior to FWI, after FWI and after FWI but co-rendered with the seismic data in the background. Note that the stratigraphic and structural details in the FWI velocity model are consistent with the seismic data. Data courtesy of Shell NZ.

Cross section (in depth) through a pre- and post-FWI velocity model, co-rendered with the seismic data. Note the additional stratigraphic detail in the post-FWI model including pinchouts, channels, better conformability and better match to the well data.