Seismic interferometry-turning noise into signal

By Andrew Curtis, Peter Gerstoft, Haruo Sato, Roel Snieder, Kees Wapenaar. 2006

444 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Geophysics

View Paper: https://www.semanticscholar.org/paper/6bb52517e0ca2c8266aeaa2ba58f6aa4e16f9c84

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

In Geophysics

Citations in the corpus

Data-driven wavefield focusing and imaging with multidimensional deconvolution: Numerical examples for reflection data with internal multiples (2014, background): “As in seismic interferometry (Curtis et al., 2006; Schuster, 2009), one of our goals is to retrieve the response to a virtual source inside an unknown medium and then use this response to build an image of the subsurface, hence, going beyond the single-scattering assumption.”
Tutorial on seismic interferometry: Part 2 — Underlying theory and new advances (2010, methodology): “Also, the surface-wave-removal methods of Dong et al. 2006 , Curtis et al. 2006 , and Halliday et al. 2007, 2010a require physically recorded and interferometrically constructed Green’s function estimates between the locations of an active source and active receiver.”
Interferometry by deconvolution. Part 1 -Theory for acoustic waves and numerical examples (2008, unknown): “Curtis et al. !”
Tutorial on seismic interferometry: Part 1 — Basic principles and applications (2010, background): “Surface waves can be predicted by interferometry and subsequently subtracted from exploration seismic data Curtis et al. (2006); Dong et al. (2006a); Halliday et al. (2007); Xue et al. (2009); Halliday et al. (2010).”
Focusing the wavefield inside an unknown 1D medium: Beyond seismic interferometry (2012, background): “First, with seismic interferometry (Weaver and Lobkis, 2001; Wapenaar et al., 2005; Curtis et al., 2006; Schuster, 2009) it is possible to retrieve the response to a virtual source inside the medium with a receiver at the position where the virtual source is to be created, assuming the medium is…”
Body wave extraction and tomography at Long Beach, California, with ambient‐noise interferometry (2015, methodology): “Seismic interferometry, one type of cross-correlation analyses, is a powerful tool to extract Earth response from passive data at the local and global scales [e.g., Curtis et al., 2006; Ruigrok et al., 2010; Nakata and Snieder, 2011; Boué et al., 2014].”
Seismic interferometry, surface waves and source distribution (2008, methodology): “D Rayleigh wave orthogonality relationship, derived from a representation theorem of the convolution type (de Hoop 1995, eq.”