Improvement of the algorithm for adaptive separation of the vibroseis signal from its harmonics in case of strong additive noise
https://doi.org/10.18303/2619-1563-2022-1-49
Abstract
An algorithm for separating a vibroseis signal from its harmonics implies preliminary prediction of harmonics with their subsequent adaptive subtraction from the correlogram. To obtain the adaptation filter estimates, a statistical criterion is used that minimizes the energy of the subtraction result. The amplitudes of the signals in a seismic trace decay due to geometrical spreading, which leads to statistical inhomogeneity in the objective formed. Therefore, an increase in the statistical reliability of estimation should be associated with an increase in signal amplitudes at large recording times. On the other hand, the source records always contain additive noise, and the signal-to-noise ratio decreases at longer times. In order to provide a compromise between the growth of signal amplitudes and maintaining a satisfactory signal-to-noise ratio in the operator adjusting gate, self-tuning weighting functions are included into the objective. A method for modifying the objective is proposed, which enables increased performance of the algorithm.
About the Authors
M. S. Denisov
GEOLAB Ltd
Russian Federation
Russian Federation
Ordzhonikidze Str., 12/4, Moscow, 119071
A. A. Zykov
GEOLAB Ltd
Russian Federation
Russian Federation
Ordzhonikidze Str., 12/4, Moscow, 119071
References
1. Boganik G.N., Gurvich I.I. Seismic Exploration [in Russian]. – AIS, Tver, 2006. – 744 p.
2. Denisov M.S. Efficient and robust estimators of autocorrelation functions // Geology, Geophysics and Development of Oil Deposits. – 1992. – Vol. 12. – P. 12–16.
3. Denisov M.S., Finikov D.B. Method for aliasing attenuation during seismic data summation (on the example of modeling multiple reflections) // Geofizika. – 2005. – Vol. 1. – P. 12–16.
4. Denisov M.S., Shneerson M.B. Utilization of harmonics to broaden the bandwidth in Vibroseismic. Part 2. // Seismic Technologies. – 2017. – Vol. 3. – P. 36–54.
5. Denisov M.S., Shneerson M.B. Nature of harmonics in the Vibroseis method and the possibility of their utilization to broaden the signal frequency band // Geofizika. – 2018. – Vol. 3. – P. 24–27.
6. Denisov M.S., Egorov A.A. Constructing a model of vibroseis signal complicated by harmonics // Russian Journal of Geophysical Technologies. – 2019а. – Vol. 1. – P. 72–83, doi: 10.18303/2619-1563-2019-1-72.
7. Denisov M.S., Egorov A.A. Optimization-based recursive filtering for vibroseis harmonic noise elimination // Russian Journal of Geophysical Technologies. – 2019b. – Vol. 2. – P. 23–53, doi: 10.18303/2619-1563-2019-2-23.
8. Denisov M.S., Zykov A.A. Study of properties of real vibroseis signals contaminated by harmonic noise // Russian Journal of Geophysical Technologies. – 2022. – Vol. 1. – P. 30–48, doi: 10.18303/2619-1563-2022-1-30.
9. Denisov M.S., Egorov A.A., Shneerson M.B. Testing the optimization-based recursive filtering algorithm to suppress harmonics on model and field correlograms // Russian Journal of Geophysical Technologies. – 2019. – Vol. 2. – P. 54–66, doi: 10.18303/2619-1563-2019-2-54.
10. Denisov M.S., Egorov A.A., Shneerson M.B. Optimization‐based recursive filtering for separation of signal from harmonics in vibroseis // Geophysical Prospecting. – 2021. – Vol. 69 (4). – P. 779–798, doi: 10.1111/1365-2478.13084.
11. Djigan V.I. Fast multichannel RLS-algorithm with regularization and stabilization // Electronics (Izvestiya vuzov). – 2004. – Vol. 1. – P. 83–90.
12. Guitton A., Verschuur D.J. Adaptive subtraction of multiples using the L1–norm // Geophysical Prospecting. – 2004. – Vol. 52 (1). – P. 27–38, doi: 10.1046/j.1365-2478.2004.00401.x.
13. Kondratiev I.K. Linear processing systems in seismic exploration [in Russian]. – Nedra, Moscow, 1976. – 175 p.
14. Korn G., Korn T. Handbook of mathematics [in Russian]. – Nauka, Moscow, 1974. – 832 p.
15. Malkin A.L. Non-Gaussian statistical model of seismic trace // Russian Geology and Geophysics. – 1989. – Vol. 30 (1). – P. 105–115.
16. Marple Jr. S.L. Digital spectral analysis and its applications [in Russian]. – Mir, Moscow, 1990. – 584 p.
17. Rapoport M.B. Computing technology in field geophysics [in Russian]. – Nedra, Moscow, 1993. – 352 p.
18. Robinson E., Treitel S. Digital signal processing in geophysics, in: Oppenheim E. (Ed.), Application of digital signal processing [in Russian]. – Mir, Moscow, 1980. – P. 486–544.
19. Rozemond H.J. Slip-sweep acquisition // 66th SEG Annual Meeting and Exposition: Expanded Abstracts. – Denver, 1996. – P. 64–67, doi: 10.1190/1.1826730.
20. Shubik B.M. Principles of building self-adjusting seismic data processing procedures // Geology and Mineral Resources of Siberia. – 2011. – Vol. 3. – P. 39–47.
21. Vedernikov G.V., Maksimov L.A., Zharkov A.V. Study of multiple harmonics of vibroseis signals // Geofizika. – 2001. – Special Issue to 30th Anniversary of “Sibneftegeophysica”. – P. 33–38.
22. Walden A.T. Non‐Gaussian reflectivity, entropy, and deconvolution // Geophysics. – 1985. – Vol. 50 (12). – P. 2297–2904, doi: 10.1190/1.50120001.1.
Review
For citations:
Denisov M.S., Zykov A.A. Improvement of the algorithm for adaptive separation of the vibroseis signal from its harmonics in case of strong additive noise. Russian Journal of Geophysical Technologies. 2022;(1):49-75. (In Russ.) https://doi.org/10.18303/2619-1563-2022-1-49
Views:
241
Email this article 