Abstract
SUMMARYFull-waveform inversion (FWI) is an effective tool to retrieve a high-resolution subsurface velocity model. The source wavelet accuracy plays an important role in reaching that goal. So we often need to estimate the source function before or within the inversion process. Source estimation requires additional computational cost, and an inaccurate source estimation can hamper the convergence of FWI. We develop a source-independent waveform inversion utilizing a recently introduced wavefield reconstruction based method, which we refer to as efficient wavefield inversion (EWI). In EWI, we essentially reconstruct the wavefield by fitting it to the observed data as well as a wave equation based on iterative Born scattering. However, a wrong source wavelet will induce errors in the reconstructed wavefield, which may lead to a divergence of this optimization problem. We use a convolution-based source-independent misfit function to replace the conventional data fitting term in EWI to formulate a source-independent EWI (SIEWI) objective function. By convolving the observed data with a reference trace from the predicted data and convolving the predicted data with a reference trace from the observed data, the influence of the source wavelet on the optimization is mitigated. In SIEWI, this new formulation is able to mitigate the cycle-skipping issue and the source wavelet uncertainty simultaneously. We demonstrate those features on the Overthrust model and a modified Marmousi model. Application on a 2-D real data set also shows the effectiveness of the proposed method.
Highlights
Full-waveform inversion (FWI) is a highly non-linear problem which aims at minimizing the misfit between predicted and observed data to retrieve a high-resolution velocity model (Tarantola 1984; Pratt et al 1998; Virieux & Operto 2009)
Wavefield reconstruction inversion (WRI) was proposed to reduce the cycle-skipping issue by relaxing the wave equation constraint transforming it to a regularization term (Leeuwen & Herrmann 2013, 2015)
We find that wavefield reconstruction based methods (WRI and efficient wavefield inversion (EWI)) are more vulnerable to the wrong source function, so we repeat the no inverse crime inversion using FWI with the same inversion setup
Summary
Full-waveform inversion (FWI) is an effective tool to retrieve a high-resolution subsurface velocity model. We develop a sourceindependent waveform inversion utilizing a recently introduced wavefield reconstruction based method we refer to as efficient wavefield inversion (EWI). In EWI, we essentially reconstruct the wavefield by fitting it to the observed data as well as a wave equation based on iterative Born scattering. We use a convolution-based source-independent misfit function to replace the conventional data fitting term in EWI to formulate a source-independent EWI (SIEWI) objective function. In SIEWI, this new formulation is able to mitigate the cycle-skipping issue and the source wavelet uncertainty, simultaneously. We demonstrate those features on the Overthrust model and a modified Marmousi model.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have