Suppress random seismic noise by edge-preserving polynomial fitting method

Abstract

The separation of signal and noise is a central issue in seismic data processing. We perform an edge-preserving polynomial fitting (EPPF) method to suppress random noise and preserving signals and edges. This method assumes that a 1D signal can be modeled by a polynomial. To estimate any sample in a 1D signal, a series of shifted windows are used and the window with the minimum fitting error is selected and its output is assigned as the final estimate for this sample. In 2D seismic data, several 1D signals are extracted along different directions and then are processed by the EPPF method. we select the direction with a minimum fitting error and select its output as the final estimate for this point. Applications with synthetic and real data sets show that the EPPF method suppresses the random seismic noise effectively while preserving the signals and edges.