Marchenko imagingMarchenko imaging

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Data-driven wavefield focusing and imaging with multidimensional deconvolution: Numerical examples for reflection data with internal multiples (2014, methodology): “Additionally, if we want to image a portion of the subsurface that is located between complicated overburden and underburden, we can take advantage of data-driven wavefield focusing to retrieve the reflection response from below (Wapenaar et al., 2014b).”
Internal multiple prediction and removal using marchenko autofocusing and seismic interferometry (2015, background): “Autofocusing also allows one to perform Marchenko redatuming of reflectivity to a finite number of depth levels and apply standard imaging in between these redatuming levels (Wapenaar et al., 2014).”
Adaptive overburden elimination with the multidimensional Marchenko equation (2016, methodology): “This is done by substitution of equation 19 into equation 20, yielding fΩ͡δgðχA; χP; tÞ ¼ v͡þmðχA; χP; tÞ − fΩv͡þmgðχA; χP; tÞ; (21) with the kernel Ω ¼ Θt2t0R⋆Θt2t0R: (22) Similar to the Marchenko equation of Wapenaar et al. (2014a), equation 21 is a Fredholm integral equation of the second kind, w”