Multichannel signal interpolation in the presence of spatial aliasing

Steep seismic linear events are often aliased due to spatial undersampling of wave fields creating different kinds of coherent noises and adversely affecting migration. To avoid the expensive costs of high resolution spatial sampling, seismic traces are interpolated. Trace interpolation, if successful, can effectively improve migration and reduce the coherent noises. An algorithm, based on a narrowband multichannel model to spatially interpolate equally spaced seismic traces, in the presence of noise, is considered. The algorithm interpolates N-1 virtual traces based on the outputs of N real traces originally sampled at less than the spatial Nyquist rate. This is done by solving a set of N forward backward linear prediction equations that relate the known (real) traces to the unknown (virtual) traces. This method, unlike the method presented by S. Spitz (1991), is not susceptible to the temporal frequency content of the data and generates less interpolation error. Simulation results that validate the performance and usefulness of this algorithm in interpolating seismic events in the presence of severe spatial aliasing are provided