Reconstruction of Compressively-Sampled Land Data
A. Alfaraj (TU Delft - Applied Sciences)
D.J. Verschuur (TU Delft - Civil Engineering & Geosciences)
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Abstract
Acquiring economical land data with compressive sensing requires data reconstruction. In the presence of complex near-surface weathering layers, which on their own typically pose a challenge to processing densely sampled data, data reconstruction suffers. The conventional approach of near-surface correction followed by interpolation rely on knowledge of the subsurface. However, obtaining a velocity model is difficult from subsampled data influenced by the weathering layers. To avoid that, we propose to reconstruct the data with a model-independent rank-reduction-based near-surface correction followed by interpolation. We showcase the proposed reconstruction on synthetic data. A field data example will also be presented during the meeting to demonstrate the potential of the method.