Upgoing body waves that travel through a heterogeneous near-surface region can excite scattered waves. When the scattering takes place close to the receivers, secondary waves interfere with the upcoming reflections, diminishing the continuity of the wavefront. We estimate a near-surface scattering distribution from a subset of a data record and use this scattering distribution to predict the secondary waves of the entire data record with a wave-theoretical model for near-receiver scattering. We then subtract the predicted scattered waves from the record to obtain the wavefield that would have been measured in the absence of near-surface heterogeneities. We apply this method to part of a field data set acquired in an area with significant near-surface heterogeneity. The main result of our processing scheme is that we effectively remove near-surface scattered waves. This, in turn, increases trace-to-trace coherence of reflection events. Moreover, application of our method improves the results obtained from just an application of a dip filter because we remove parts of the scattered wave with apparent velocities that are typically accepted by the pass zone of the dip filter. Based on these results, we conclude that our method for suppressing near-receiver scattered waves works well on densely sampled land data collected in areas with strong near-surface heterogeneity.