  Full waveform inversion is a high-resolution subsurface imaging technique, in
which full seismic waveforms are used to infer subsurface physical properties.
We present a novel, target-enclosing, full-waveform inversion framework based
on an interferometric objective function. This objective function exploits the
equivalence between the convolution and correlation representation formulas,
using data from a closed boundary around the target area of interest. Because
such equivalence is violated when the knowledge of the enclosed medium is
incorrect, we propose to minimize the mismatch between the wavefields
independently reconstructed by the two representation formulas. The proposed
method requires only kinematic knowledge of the subsurface model, specifically
the overburden for redatuming, and does not require prior knowledge of the
model below the target area. In this sense it is truly local: sensitive only to
the medium parameters within the chosen target, with no assumptions about the
medium or scattering regime outside the target. We present the theoretical
framework and derive the gradient of the new objective function via the
adjoint-state method and apply it to a synthetic example with exactly redatumed
wavefields. A comparison with FWI of surface data and target-oriented FWI based
on the convolution representation theorem only shows the superiority of our
method both in terms of the quality of target recovery and reduction in
computational cost.
