@inproceedings{3d3b5a1ecaf04037bc614bf5cf8189a0,

title = "Elastic reflectivity preserving full-wavefield inversion",

abstract = "Due to the non-linearity and high-computational costs associated with Elastic full-waveform inversion (FWI), it is still avoided at large and acoustic wave equation-based forward modeling algorithms are used in FWI to explain the elastic data, which in turn are not able to correctly explain the true elastic amplitudes. Thus, it{\textquoteright}s output is then used in conventional migration methods to explain the elastic reflection amplitudes (Rpp). In this paper, we present a data-driven inversion algorithm (Full Wavefield Migration) based on Full Wave-field Modeling (FWMod), which can go one step ahead of its forward model, unlike FWI, to explain the correct elastic reflection amplitudes (Rpp) present in data without explilicty imposing the elastic wave equation. They inherently explain the true reflectivity corresponding to the type of input data (acoustic or elastic), which are comparable to the theoretical reflection coefficients. This elastic Rpp estimation can easily be coupled with automatic velocity update using another FWMod-based algorithm, called Joint Migration Inversion",

keywords = "depth migration, internal multiples, reflection, elastic, modeling",

author = "Aayush Garg and D.J. Verschuur",

year = "2017",

doi = "10.1190/segam2017-17786449.1",

language = "English",

series = "SEG Technical Program Expanded Abstracts 2017",

publisher = "SEG",

pages = "5561--5566",

booktitle = "SEG Technical Program Expanded Abstracts 2017",

}