A reflection-based efficient wavefield inversion

Abstract

Full-waveform inversion (FWI) is popularly used to obtain a high-resolution subsurface velocity model. However, it requires either a good initial velocity model or low-frequency data to mitigate the cycle-skipping issue. Reflection-waveform inversion (RWI) uses a migration/demigration process to retrieve a background model that can be used as a good initial velocity in FWI. The drawback of the conventional RWI is that it requires the use of a least-squares migration, which is often computationally expensive, and is still prone to cycle skipping at far offsets. To improve the computational efficiency and overcome the cycle skipping in the original RWI, we incorporate it into a recently introduced method called efficient wavefield inversion (EWI) by inverting for the Born scattered wavefield instead of the wavefield itself. In this case, we use perturbation-related secondary sources in the modified source function. Unlike conventional RWI, the perturbations are calculated naturally as part of the calculation of the scattered wavefield in an efficient way. As the sources in the reflection-based EWI (REWI) are located in the subsurface, we are able to update the background model along the reflection wave path. In the background velocity inversion, we calculate the background perturbation by a deconvolution process at each frequency. After obtaining the REWI inverted velocity model, a sequential FWI or EWI is needed to obtain a high-resolution model. We demonstrate the validity of the proposed approach using synthetic data generated from a section of the Sigsbee2A model. To further demonstrate the effectiveness of the proposed approach, we test it on an ocean bottom cable (OBC) dataset from the North Sea. We find that the proposed methodology leads to improved velocity models as evidenced by flatter angle gathers.

Frequency-domain reflection waveform inversion with generalized internal multiple imaging

“…Alkhalifah and Wu (2016) introduce a new RWI misfit function, which admits the diving/refraction wave update in the gradient, to provide a natural transition from RWI and FWI. Song and Alkhalifah (2021) obtained the tomographic component using the RWI machinery under the wavefield inversion frame. Nevertheless, there is still an elusive middle wavenumber gap defined by the maximum scattering angle and the length of the wavepath between the RWI and FWI (Alkhalifah et al, 2018;Audebert and Ortiz-Rubio, 2018).…”