High-Resolution One-Way Reflection Waveform Inversion

Abstract

Reflection waveform inversion (RWI) is a method that relies on primary pure reflection data to recover the subsurface background velocity based on the associated evolving seismic images. Background velocity updates estimated by conventional RWI are nonoptimal, which is partly attributed to low-resolution tomographic wavepaths and migration isochrones. Preconditioning RWI sensitivity kernels using Hessian information solves this problem but is not practical for a large number of model parameters. One-way reflection waveform inversion (ORWI) is a reflection waveform tomography technique in which the forward modeling scheme operates in one direction (downward and then upward) via virtual parallel data levels in the medium. The ORWI framework allows us to break down the Hessian matrix into smaller operators, which makes the preconditioning operation more efficient and less computationally expensive. This extended abstract turns conventional ORWI into a high-resolution but computationally feasible ORWI (Gauss-Newton ORWI) to improve the nonoptimal background velocity updates.