  While wavefield reconstruction through weighted low-rank matrix
factorizations has been shown to perform well on marine data, out-of-the-box
application of this technology to land data is hampered by ground roll. The
presence of these strong surface waves tends to dominate the reconstruction at
the expense of the weaker body waves. Because ground roll is slow, it also
suffers more from aliasing. To overcome these challenges, we introduce a
practical workflow where the ground roll and body wave components are recovered
separately and combined. We test the proposed approach blindly on a subset of
the 3D SEAM Barrett dataset. With our technique, we recover densely sampled
data from 25 percent randomly subsampled receivers. Independent comparisons on
a single shot demonstrate significant improvements achievable with the
presented workflow.
