Subsurface wavefields based on the generalized internal multiple imaging

Abstract

Accessing full Green's functions between image points and the location of our recording surface is crucial to obtaining accurate subsurface wavefields and accurate images beyond the single scattering assumption. A direct approach to do so is oered by utilizing the recorded data combined with a background model. The process includes extrapolating the recorded data back in time followed by a simple interferometric crosscorrelation of the back propagated wavefield with the recorded data. This interferometric step oers the opportunity to extract subsurface Green's functions with the first order scattering forming the transmission component, and the second-order scattering becomes the leading scattering term. A crosscorrelation of the resulting, assumed upgoing, wavefield with a forward modeled down going wavefield highlights the double scattered reflectivity in a process referred to as the generalized internal multiple imaging (GIMI). The resulting image is vulnerable to crosstalk between dierent order multiples interacting with each other. Thus, we develop the adjoint GIMI that takes us from image to data, and use it to formulate a least square optimization problem to fit the image to the data. The result is reduced crosstalk and cleaner higher resolution multiple scattering images. We also extract space extensions of the image, which oers the opportunity to evaluate the focussing capability of the velocity model, and formulate updates for that model based on double scattering.