Application of the recursive approaching signal filter (RASF) to VSP (vertical seismic profiling) data processing

Abstract

The Recursive Approaching Signal Filter (RASF) is a newly developed filtering technique which combines many advantages of linear, non-linear and adaptive filters. It not only allows step functions to pass without altering them, but also removes noise, such as Gaussian and Laplacian distributed noise fairly well. When applied to Vertical Seismic Profiling (VSP) data processing, the RASF emphasizes the abrupt discontinuities which originate or terminate at discrete depth points. By simply changing a parameter, the RASF may be transformed into a desired filter in order to achieve the maximum utilization of VSP field data, especially if the application requires an analysis of upgoing primary reflection waves. When evaluated with synthetic VSP modeling data and the same data corrupted by additive white Gaussian noise (AWGN), the RASF compares favorably to the ƒ-k velocity filtering and median filtering with regard to noise removal, while keeping step functions and achieving computational simplicity.