Misfit functions for full waveform inversion based on instantaneous phase and envelope measurements
By Ebru Bozdag, Jeannot Trampert, Jeroen Tromp. 2011
381 citations recorded by the source corpus.
Subfields: Geophysics, Ocean Engineering
View Paper: https://www.semanticscholar.org/paper/927cd635247d172de7c9a6bf2ee46c6d17e6a10a
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Geophysics
- Andreas Fichtner
- Jeannot Trampert
- Jeroen Tromp
- Romain Brossier
- Jean Virieux
- Ludovic Métivier
- Ebru Bozdag
- Qinya Liu
In Ocean Engineering
- Andreas Fichtner
- Romain Brossier
- Stéphane Operto
- Jean Virieux
- Ludovic Métivier
- Jeannot Trampert
- Jeroen Tromp
- Ebru Bozdag
Citations in the corpus
- Full Waveform Inversion and the Truncated Newton Method (2013, methodology): “Cross-correlation of observed and synthetic data [38], comparison of the instantaneous phase and envelope of the signals [19, 7], deconvolution approaches where Wiener filters are used to match observed and predicted data [37, 77, 80], and image-domain techniques [72] are all instances of these atte”
- Multiscale full waveform inversion (2013, positive): “1 , (2) the comparison of the synthetic and observed seismograms using a suitable mis-fit measure (e.g. Crase et al. 1990; Fichtner et al. 2008; Brossier et al. 2010; Bozda˘g et al. 2011), (3) the computation of sensitivity kernels and a descent direction with the help of adjoint techniques (e.g.…”
- Seismic envelope inversion and modulation signal model (2014, neutral): “Bozdag et al. (2011) discuss the envelope misfit functional and its use in the kernel sensitivity analysis of global seismic tomography.”
- Deep-Learning Inversion of Seismic Data (2019, background): “…FWI, geophysicists have proposed many improvements, such as the multiscale strategy [9]–[12], processing of seismic data in other domain [13], [14], etc. Recently, Deep Neural Networks (DNNs) have demonstrated remarkable ability to approximate nonlinear mapping function between various data…”
- Multiscale adjoint waveform tomography for surface and body waves (2015, methodology): “Reducing the nonlinearity of waveform inversion problems involves a judicious choice of the objective function (Luo and Schuster , 1991; Gee and Jordan, 1992; Dahlen and Baig, 2002; Fichtner et al., 2008; Bozdağ et al., 2011; Rickers et al., 2012; Masoni et al., 2014).”
- Resolution analysis in full waveform inversion (2011, methodology): “…methodology is the design of objective functionals, commonly constructed to meet criteria in the data space, such as robustness (Crase et al. 1990; Brossier et al. 2010) and separation of phase and amplitude (Luo & Schuster 1991; Gee & Jordan 1992; Fichtner et al. 2008; Bozdağ et al. 2011).”
- Global adjoint tomography: first-generation model (2016, background): “The adjoint source term is directly dependent on the chosen misfit function (e.g. Tromp et al. 2005; Bozdağ et al. 2011), such that the resulting Fréchet derivative, or sensitivity kernel, reflects the measurement.”
- Analysis of optimal transport and related misfit functions in full-waveform inversion (2017, background): “Other misfit functions proposed in literature (Brossier et al., 2010; Bozdag et al., 2011), include the Huber norm (Ha et al., 2009), filter-based misfit functions (Warner and Guasch, 2014; Zhu and Fomel, 2016), seismic envelop inversion (Luo and Wu, 2015), etc.”
- AxiSEM: broadband 3-D seismic wavefields in axisymmetric media (2014, background): “Most modern measurements of “traveltimes”, such as cross-correlation (Nolet, 2008), time–frequency phase delays (Fichtner et al., 2008), or instantaneous phase (Bozdag et al., 2011) are based on waveforms, and therefore necessitate full wavefield modeling.”