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

• Published in: Journal of applied geophysics Vol. 132; pp. 33 - 37
• Main Authors: Rekapalli, Rajesh, Tiwari, R.K.
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.09.2016
• Subjects: Eigenvectors; Frequency filtering; Seismic reflection data; Singular spectral analysis; Seismic reflection data; Eigenvectors; Singular spectral analysis; Frequency filtering
• ISSN: 0926-9851; 1879-1859
• DOI: 10.1016/j.jappgeo.2016.06.009

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. •We introduce a new Weighted Eigen Spectrogram based SSA filtering algorithm.•The underlying advancement simplifies the grouping process in the filtering operation.•Tested the method on synthetic data assorted with field simulated noise•Demonstrated the filtering efficiency of the algorithm on seismic reflection field data