Multifrequency beam-based migration in inhomogeneous media using windowed Fourier transform frames

Ram Tuvi*, Zeyu Zhao, Mrinal K. Sen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

We consider the problem of inhomogeneous subsurface imaging using beam waves. The formulation is based on the ultra-wide-band phase-space beam summation (UWB-PS-BS) method, which is structured upon windowed Fourier transform (WFT) expansions of surface fields and sources. In this approach, the radiated field is given as a superposition of beam propagators. Here, we use the beams first for expanding the surface sources and the scattered data, and then for imaging where we use the backpropagation and cross-correlation of beams. This formulation enables a target oriented imaging approach, where we take into account only pairs of source and receiver beams that pass near a region of interest, and thus extract only the relevant data arriving from this region. It also leads to a priori sparse representation of both the beam domain data and the beam propagators. A physical cogent for the beam domain data is obtained under the Born approximation. The beam domain data can be approximated as the local interaction between the beam propagators and the medium reflectivity. Thus, one may interpret the beam domain data as a local Snell's law reflection in the direction defined by the vector summation of the incident beam and backpropagated beam ray parameters. We demonstrate a physical model for the beam domain data and the salient features of the proposed imaging algorithm using numerical examples.

Original languageEnglish
Pages (from-to)1086-1099
Number of pages14
JournalGeophysical Journal International
Volume223
Issue number2
DOIs
StatePublished - 1 Nov 2020
Externally publishedYes

Keywords

  • Inverse theory
  • Wave propagation
  • Wavelet transform

Fingerprint

Dive into the research topics of 'Multifrequency beam-based migration in inhomogeneous media using windowed Fourier transform frames'. Together they form a unique fingerprint.

Cite this