Focusing the wavefield inside an unknown 1D medium: Beyond seismic interferometry
By F. Broggini, Roel Snieder, Kees Wapenaar. 2012
163 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Geophysics
View Paper: https://www.semanticscholar.org/paper/b3bd999d4e01fd21acf420076062a16a0fb6b552
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Kees Wapenaar
- Evert C. Slob
- Roel Snieder
- Andrew Curtis
- F. Broggini
- J. Neut
- Michel Campillo
- N. M. Shapiro
In Geophysics
- Kees Wapenaar
- Roel Snieder
- Evert C. Slob
- Andrew Curtis
- F. Broggini
- C. D. C. Filho
- K. Löer
- Giovanni Angelo Meles
Citations in the corpus
- Internal multiple prediction and removal using marchenko autofocusing and seismic interferometry (2015, background): “Marchenko autofocusing estimates up- and downgoing components of Green’s functions between virtual (imagined) source locations inside a medium and real receivers at the surface (Broggini et al., 2012; Wapenaar et al., 2012, 2013).”
- Seismic reflector imaging using internal multiples with Marchenko-type equations (2014, methodology): “Recently, Broggini et al. (2012) used the idea to retrieve a virtual vertical seismic profile (VSP) with the virtual source inside the layered medium at any depth location and the receivers at the surface.”
- Data-driven wavefield focusing and imaging with multidimensional deconvolution: Numerical examples for reflection data with internal multiples (2014, unknown): “Following recent work (Broggini et al., 2012; Wapenaar et al., 2012a), we briefly introduce the theory of data-driven wavefield focusing for 2D media and illustrate it with a numerical example in an inhomogeneous medium shown in Figure 1a.”