FWI can be used as part of any Prestack Depth Migration (PSDM) velocity model building workflow with virtually no time impact.
As FWI uses raw data, either shot or receiver gathers, it can be deployed early in the model building process. The input data requires minimum pre-processing, enabling an accelerated turnaround when compared to conventional techniques. Any ree-surface effects can be left in the data.
The method begins with an initial starting model which is then iteratively improved using a sequence of linearized inversions, to solve the full non-linear 3D FWI problem.
New Flavors Abound
As computing power expands, so has the seismic data frequency range on which FWI is run. While the greatest benefit for model building is achieved from access to relatively low frequencies (<20 Hz), increasing the frequency content in FWI may help in reservoir characterization.
Obtaining full-bandwidth, absolute elastic-attributes for lithology and fluid prediction requires a low-frequency model. The lower frequency component required for absolute modeling can be generated from velocities, assuming they contain sufficient resolution. This reduces the emphasis on the well and seismic information. This can make a vital difference in exploration settings. Less a prior input is an advantage in attribute prediction and ensures that the results of pre-stack seismic inversion are primarily data-driven.
Using a broader frequency content to obtain the FWI model can provide the lower frequency component for elastic property generation. Well information becomes a control point. This allows reservoir geoscientists to confidently derive reliable elastic attributes, such as acoustic impedance and Vp/Vs ratios, away from the well locations.