F-x Nonstationary Seismic Data Interpolation Using Complex Nonstationary Autoregression

We have proposed a novel method for seismic trace interpolation using f-x regularization nonstationary autoregression (f-x RNA). f-x RNA interpolation can deal with the events which have space-varying dips because the estimated f-x RNA coefficients are smoothly dependent on space direction. This method includes two steps: the estimation of f-x RNA coefficients and the reconstruction missing traces using estimated f-x RNA. Similar to Spitz’s f-x interpolation, we also use f-x RNA estimated from low frequency components to obtain f-x RNA of aliased high frequency components. We implement the algorithm by iterated scheme using complex-numbers conjugate gradient method. The applicability of the proposed method is examined using synthetic and field data examples.