Full waveform inversion of blended surface-related multiple orders

ABSTRACT Full-waveform inversion (FWI) is capable of handling various wave types, for example, primary reflections, direct waves, diving waves, and multiple reflections. However, FWI often encounters high nonlinearity when the starting velocity model significantly deviates from the true velocity, and the existence of multiples can further worsen this situation. As a result, the objective function may be trapped in a local minimum, causing the inversion process to fail to converge to the global minimum. Constructing an objective function by decomposing multiples into different controlled orders and performing the FWI on multiples with consecutive orders can expedite convergence. However, conducting the FWI using multiples in an order-by-order way may result in high computational cost. This study addressed this challenge by creating virtual sources and supergathers. These supergathers phase-encode many orders of multiples and integrate them into one for FWI, requiring only one FWI for all orders of multiples. By using such a random phase-encoding scheme, crosstalk artifacts arising from interferences between mismatched multiple orders in the source and receiver wavefields can be largely mitigated. The proposed method was validated through numerical experiments with a synthetic data set, as well as using marine field data from Madagascar. The results demonstrate that FWI using phase-encoded multiples significantly improves convergence while maintaining computational efficiency.