Type
Conference PaperKAUST Department
Earth Science and Engineering ProgramPhysical Science and Engineering (PSE) Division
Seismic Wave Analysis Group
Date
2017-05-26Online Publication Date
2017-05-26Print Publication Date
2017-06-12Permanent link to this record
http://hdl.handle.net/10754/624987
Metadata
Show full item recordAbstract
The lack of low frequency information in the acquired data makes full waveform inversion (FWI) conditionally converge to the accurate solution. An initial velocity model that results in data with events within a half cycle of their location in the observed data was required to converge. The multiplication of wavefields with slightly different frequencies generates artificial low frequency components. This can be effectively utilized by multiplying the wavefield with itself, which is nonlinear operation, followed by a smoothing operator to extract the artificially produced low frequency information. We construct the objective function using the nonlinearly smoothed wavefields with a global-correlation norm to properly handle the energy imbalance in the nonlinearly smoothed wavefield. Similar to the multi-scale strategy, we progressively reduce the smoothing width applied to the multiplied wavefield to welcome higher resolution. We calculate the gradient of the objective function using the adjoint-state technique, which is similar to the conventional FWI except for the adjoint source. Examples on the Marmousi 2 model demonstrate the feasibility of the proposed FWI method to mitigate the cycle-skipping problem in the case of a lack of low frequency information.Citation
Li Y, Choi Y, Alkhalifah T, Li Z (2017) Full Waveform Inversion Using Nonlinearly Smoothed Wavefields. 79th EAGE Conference and Exhibition 2017. Available: http://dx.doi.org/10.3997/2214-4609.201701342.Sponsors
We thank KAUST for its support and the SWAG for collaborative environment. Author Yuanyuan Li wishes to thank the China Scholarship Council for support to study abroad.Publisher
EAGE Publicationsae974a485f413a2113503eed53cd6c53
10.3997/2214-4609.201701342