Enhancement of near-surface elastic full waveform inversion results in regions of low sensitivities

Elastic full waveform inversion of high-resolution seismic data is a potentially very powerful option for imaging the shallow subsurface. Unfortunately, the success of traditional full waveform inversion applied to such problems is limited by a very uneven sensitivity distribution, which can be attributed to the uneven amplitudes of body and surface waves. As a result, very shallow structures are well resolved by fitting the large amplitude surface waves, but the imaging quality decreases rapidly with depth. To account for uneven sensitivity distributions, we present a novel scaling approach that enhances weak sensitivities in regions of interest. To this end, the column sums of the Jacobian matrix - each of them corresponding to one model parameter - are equalized prior to updating the model. The performance of this methodology is demonstrated by inverting two synthetic, but realistic, data sets. Both the P- and S-wave velocity images were improved significantly by applying the new scaling technique. Our results are particularly relevant for shallow elastic full waveform inversion problems, but we also see benefits of our technique for other surface-based geophysical methods, such as geoelectrics or electromagnetics.