Frequency-domain prestack sparse Bayesian learning inversion method is proposed.

The method retrieves sparse P- and S-wave impedance reflectivity by adding, deleting or re-estimating operator.

Parameterized Gaussian prior helps retrieve sharp layer boundaries and precondition helps improve the inversion results.

Synthetic data and real data are adopted to demonstrate the performance of the proposed method.