Reconstruction of 2D Seismic Wavefields from Nonuniformly Sampled Sources.

In a 3D seismic survey, the source sampling in a regular grid is commonly limited by economic costs, geological constraints, and environmental challenges. This non-uniform sampling cannot be ignored since the lack of regularity leads to incomplete seismic data with missing 2D wavefields. Notice that the postprocessing tasks have been developed under the assumption that 3D seismic data are obtained from a regular sampling. Therefore, signal recovery from incomplete data becomes a crucial step in the seismic imaging processing flow. In this work, we propose a pre-processing step that includes the nonuniformly acquired wavefields in a finer regular grid, such that shot gathers are stacked considering the actual spatial location of the sources. Then, based on the 3D curvelet transform, a sparse signal recovery algorithm that considers an interpolation operator is employed in order to reconstruct the missing wavefields in a regular grid. The performance of the proposed seismic reconstruction approach is evaluated on a real data set.