Singular spectral analysis based filtering of seismic signal using new Weighted Eigen Spectrogram

Filtering of non-stationary noisy seismic signals using the fixed basis functions (sine and cosine) generates artifacts in the final output and thereby leads to wrong interpretation. In order to circumvent the problem, we propose here, a new Weighted Eigen Spectrogram (WES) based robust time domain Singular Spectrum Analysis (SSA) frequency filtering algorithm. The new WES is used to simplify the Eigen triplet grouping procedure in SSA. We tested the robustness of the algorithm on synthetic seismic data assorted with field-simulated noise. Then we applied the method to filter the high-resolution seismic reflection field data. The band pass filtering of noisy seismic records suggests that the underlying algorithm is efficient for improving the signal to noise ratio (S/N) and also it is user-friendly.