Paper Summary
Overcoming cycle-skipping in Full Waveform Inversion (FWI) is a significant step toward enabling automation in velocity model building. This reduces the demand of acquiring very low-frequency data and/or starting the inversion procedure from kinematically accurate models. We present a new FWI method that uses time-warping as the extension domain to overcome cycle-skipping. The warping function dynamically transports the recorded field data to the modeled data and is imposed to represent the actual physical time. Thus, the derived objective function allows the inversion of the two parameters involved, model and time-warping extension, in a single optimization problem, whose solution is provided by the Alternate Direction Method (ADM). The novel FWI objective function enables automatic transition from a pure time-shift problem to a conventional least-squares one. We successfully apply the new FWI method to both synthetic and field data sets to demonstrate its effectiveness starting from inaccurate initial models. Results show the benefits of the new FWI approach in reducing the turnaround time for building high-resolution models from very simple initial velocity models.