Mitigating the near-surface effect in velocity and reflectivity estimation with multi-scale low-rank approximated image updates

Land seismic data is usually affected by the presence of near-surface weathering layers. This results in undesired short- and long-wavelength wave propagation effects that need to be accounted for in order to obtain accurate and undistorted subsurface models. While correcting for the near-surface effect prior to estimating the models of interest can provide a reasonable solution, it may as well introduce errors, e.g. when assumptions of the correction methods are not met, resulting in suboptimal models. In this work, we simultaneously estimate the subsurface models of interest, namely the velocity and reflectivity, and account for the near-surface effect during joint migration inversion (JMI). The proposed method utilizes the property that image updates obtained from inverting data without the near-surface imprint are of low-rank nature compared with those obtained from the inversion of data with the short-wavelength near-surface imprint. We demonstrate the results of our proposed method on data modelled on a complex near-surface model.