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We propose a new technique for the attenuation of locally coherent noise. We assume that the moveout of the noise is locally linear and approximate its amplitude variations with offset using piecewise (local) polynomial models. Thus, our method consists of three steps: detection of the noise (locally linear coherent noise, LLCN), amplitude estimation by a local polynomial approximation (LPA), and subtraction of the estimated coherent noise from the original data. Applying the proposed method to synthetic data and to a field data set shows that the LPA filter has good ability to model LLCN and is insensitive to the filter parameters. Comparisons of the results obtained by our method with those from the traditional frequency-wavenumber filter and the localized 2D filter in the Fourier projection domain (FPF) show that the new method outperforms both traditional methods in situations with complex coherent noise.

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