Seismic trace interpolation using half-step prediction filters

Abstract A method to perform seismic trace interpolation known as the Spitz method handles spatially aliased events. The Spitz method uses the unit-step prediction filter to estimate data spaced at Delta x/2. The missing data are obtained by solving a complex linear system of equations whose unknowns are the coefficients at the interpolated location. We attack this problem by introducing a half-step prediction filter that makes trace interpolation significantly more efficient and easier for implementation. A complex half-step prediction filter at frequency f/2 is computed in the least-squares sense to predict odd data components from even ones. At the frequency f, the prediction operator is shrunk and convolved with the input data spaced at Delta x to predict data at Delta x/2 directly. Instead of solving two systems of linear equations, as proposed by Spitz, only a system for the half-step prediction filter has to be solved. Numerical examples using a marine seismic common-midpoint (CMP) gather and a poststack seismic section were used to illustrate the new interpolation method.