Paper Summary

We present an iterative non-linear inversion method to simultaneously estimate both velocity and reflectivity. The core of the inversion workflow is a full acoustic wavefield modeling relation parameterized in terms of velocity and vector reflectivity. A key aspect is the separation of the low and high-wavenumber components of the gradient based on inverse scattering theory, enabling the sensitivity kernels to update the velocity and the vector reflectivity, respectively. The estimation problem is formulated as a multi-parameter adjoint-state inversion where the trade-off between velocity and reflectivity is minimized through scale separation. Our approach is equivalent to performing Full Waveform Inversion (FWI) and Least-Squares Reverse Time Migration (LSRTM) in a single framework using the full wavefield. The output of the inversion is a detailed velocity model together with an accurate estimate of the earth reflectivity with compensation for incomplete acquisition, poor illumination, and multiple crosstalk. The new approach reduces the turnaround time of imaging projects by combining velocity model building (FWI) and imaging (LSRTM) into a single inversion process with minimal data pre-processing.