Stanton, Aaron (University of Alberta) | Kreimer, Nadia (University of Alberta) | Bonar, David (University of Alberta) | Naghizadeh, Mostafa (University of Alberta) | Sacchi, Mauricio (University of Alberta)
A comparison is made between three 5D reconstruction methods– Projection Onto Convex Sets (POCS), Tensor Completion (TCOM), and Minimum Weighted Norm Interpolation (MWNI). A method to measure of the quality of synthetic data reconstructions is defined and applied under various scenarios. Two different measures of performance in the case of real data reconstructions are also provided and applied to a real data example taken from a land dataset acquired in the Western Canadian Sedimentary Basin. We find that TCOM and POCS are better able to reconstruct data in the presence of low SNR. We also find that TCOM provides superior results in most synthetic data scenarios, but in the case of real data reconstruction all three methods have similar performance, with POCS giving slightly better preservation of amplitudes.