A guided tour of multiparameter full-waveform inversion with multicomponent data: From theory to practice
By Stéphane Operto, Y. Gholami, V. Prieux, Alessandra Ribodetti, Romain Brossier, Ludovic Métivier, Jean Virieux. 2013
370 citations recorded by the source corpus.
Subfields: Geophysics, Ocean Engineering
View Paper: https://www.semanticscholar.org/paper/ca629e38d004be320224313948aaa3a025e10eae
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Geophysics
- Ludovic Métivier
- Romain Brossier
- Jianwei Ma
- Qiang Guo
- Fangshu Yang
- Tariq Alkhalifah
- Jean Virieux
- S. Garambois
In Ocean Engineering
- Jianwei Ma
- Romain Brossier
- Ludovic Métivier
- Fangshu Yang
- Tariq Alkhalifah
- S. Garambois
- Frederik J. Simons
- Yanhua O. Yuan
Citations in the corpus
- Multiscale adjoint waveform tomography for surface and body waves (2015, background): “Prieux et al. (2013a) (2013b) and Operto et al. (2013) discuss strategies to reduce the nonlinearity of the elastic multiparameter inversion with multicomponent data and to control the trade-off between parameters by hierarchically selecting the data components to invert and the parameter classes…”
- Elastic reflection-based waveform inversion with a nonlinear approach (2017, background): “We also devoted our attention to the latest development of multiparameter inversion (Operto et al., 2013), which included the challenges of parameter trade-off, inversion strategy, and parameterization (Wang et al., 2015; Guitton and Alkhalifah, 2016; Oh and Alkhalifah, 2016) because the EFWI…”
- Deep-learning inversion: a next generation seismic velocity-model building method (2019, methodology): “Typically, FWI is a data-fitting procedure used in reconstructing high-resolution velocity models of the subsurface, as well as other parameters that govern wave propagation, from the full information contained in seismic data (Virieux and Operto, 2009; Operto et al., 2013).”
- Two-dimensional permittivity and conductivity imaging by full waveform inversion of multioffset GPR data: a frequency-domain quasi-Newton approach (2014, background): “…advantage of our quasiNewton formulation is that it enables to update permittivity and conductivity simultaneously within the same descent step, and thus to consider the parameter trade-offs (Operto et al. 2013), unlike alternated or decoupled approaches (Ernst et al. 2007; Meles et al. 2010).”