1887
Volume 74, Issue 1
  • E-ISSN: 1365-2478

Abstract

ABSTRACT

During seismic data processing, strong single‐frequency interference noise often affects data quality. Traditional methods for single‐frequency interference identification are typically conducted in the frequency domain, primarily by searching for abnormal peaks in the frequency spectrum of each trace. However, when the interference amplitude in the frequency domain is weak relative to the entire seismic frequency, the identification process becomes significantly more challenging. To address this issue, this article proposes a time‐domain approach for identifying single‐frequency interference. First, frequency analysis is performed on seismic data containing single‐frequency interference to obtain the initial frequency , and sine and cosine signals with an amplitude of 1 at this frequency are then generated. Next, the seismic data are normalized to balance amplitude differences across different datasets in the time domain. After normalization, deep‐time seismic data are cross‐correlated with the generated sinusoidal and cosine signals, and correlation coefficient is computed to determine whether suppression is necessary. On the basis of theoretical simulations and field data analysis, suppression is considered necessary when  > 0.001. Finally, for identified single‐frequency interference, a hierarchical approximation method based on a cross‐correlation objective function is employed to search for interference frequencies with finer step sizes near the initial frequency and calculate the corresponding amplitudes. The interference signal is subsequently subtracted in the time domain to achieve interference suppression. Through synthetic experiments and the application analysis of various field seismic data (including single‐shot and stacked profiles), the proposed method demonstrates high efficiency and accuracy in identifying and suppressing single‐frequency interference.

© 2026 European Association of Geoscientists & Engineers. © 2025 European Association of Geoscientists & Engineers.
Loading

Article metrics loading...

/content/journals/10.1111/1365-2478.70120
2025-12-30
2026-02-11

  • From This Site

    /content/journals/10.1111/1365-2478.70120
    dcterms_title,dcterms_subject,pub_keyword
    -contentType:Journal -contentType:Contributor -contentType:Concept -contentType:Institution
    10
    5
Loading full text...

Full text loading...

References

  1. Bu, C.2006. “Separating 50 Hz Industry Disturbance in Geophone Domain.” Progress in Exploration Geophysics29, no. 3: 192–194. https://d.wanfangdata.com.cn/periodical/ktdqwljz200603008.
     [Google Scholar]
  2. Butler, K. E., and R. D.Russell. 1993. “Subtraction of Powerline Harmonics From Geophysical Records.” Geophysics58: 898–903. https://doi.org/10.1190/1.1443474.
     [Google Scholar]
  3. Cao, C., and R.Dai. 2003. “Identify Faint Signal Buried in Line Frequency Noise Based on Correlation Estimation.” Journal of EEE25, no. 2: 59–64. https://mall.cnki.net/magazine/article/DQDZ200302016.htm.
     [Google Scholar]
  4. Chen, K.2015. “Suppressing Scheme of Multi‐Frequency Component Industrial Interference and Its Application.” Lithologic Reservoirs27, no. 2: 92–97. https://doi.org/10.3969/j.issn.1673‐8926.2015.02.014.
     [Google Scholar]
  5. Chen, K., S.Chen, L.Li, J.Wang, Q.Wu, and X.Fan. 2014. “A High‐Accuracy Automatic Identification and Self‐Adaptive Suppression Method for Single‐Frequency Interference.” Lithologic Reservoirs26, no. 3: 109–113. https://doi.org/10.3969/j.issn.1673‐8926.2014.03.018.
     [Google Scholar]
  6. Chen, K., W.Yang, S.Chen, J.Wang, Q.Wu, and X.Fan. 2017. “High Precision Single Frequency Interference Parallel Suppressing Technique and Its Application.” Petroleum Geology and Oilfield Development in Daqing36, no. 5: 143–148. https://doi.org/10.19597/j.issn.1000‐3754.201703032.
     [Google Scholar]
  7. Chiu, S. K.2006. “Interference Cancellation by Least‐Squares Modeling and Adaptive Subtraction.” In Proceedings of the SEG Technical Program Expanded Abstracts 2006. Society of Exploration Geophysicists. https://doi.org/10.1190/1.2370096.
  8. Dong, X. T., Y.Li, and B. J.Yang. 2019. “Desert Low‐Frequency Noise Suppression by Using Adaptive DnCNNs Based on the Determination of High‐Order Statistic.” Geophysical Journal International219: 1281–1299. https://doi.org/10.1093/gji/ggz363.
     [Google Scholar]
  9. Dragoset, B.1995. “Geophysical Applications of Adaptive Noise Cancellation.” Paper Presented at the Offshore Technology Conference, Houston, Texas, May 01. https://doi.org/10.4043/7655‐MS.
  10. Duan, Y., X.Xu, and X.Gao. 2006. “The Recognition and Suppression of Single Frequency Interference Wave in Time Domain.” Geophysical and Geochemical Exploration30, no. 3: 266–269. https://www.wutanyuhuatan.com/CN/Y2006/V30/I3/266.
     [Google Scholar]
  11. Dudgeon, D. E.1977. “Fundamentals of Digital Array Processing.” Proceedings of the IEEE65: 898–904. https://doi.org/10.1109/PROC.1977.10587.
     [Google Scholar]
  12. Elboth, T., I. V.Presterud, and D.Hermansen. 2010. “Time‐Frequency Seismic Data De‐Noising.” Geophysical Prospecting58: 441–453. https://doi.org/10.1111/j.1365-2478.2009.00846.x.
     [Google Scholar]
  13. Gao, S., Z.He, B.Zhao, X.Zhou, and A.Hou. 2008. “The Self‐Adaptive Method for Identifying and Eliminating the Single‐Frequency Interference Wave.” Geophysical Prospecting for Petroleum47, no. 4: 352–356. https://www.geophysics.cn/CN/Y2008/V47/I4/352.
     [Google Scholar]
  14. Gao, S., B.Zhao, S.Zhu, G.Luo, and Z.He. 2011. “Identification and Elimination of Monofrequency Interference in Seismic Data by an Autocorrelation Algorithm.” Chinese Journal of Geophysics (in Chinese)54, no. 3: 854–861. https://doi.org/10.3969/j.issn.0001‐5733.2011.03.026.
     [Google Scholar]
  15. Gao, S., X.Zhou, and J.Cai. 2001. “Suppression of Single Frequency Interference Wave in Time Domain.” Oil Geophysics Prospecting36, no. 1: 51–55. http://www.ogp‐cn.com.cn/CN/Y2001/V36/I1/51.
     [Google Scholar]
  16. Griffith, P. G.1988. “Nonlinear Quadrature Noise Canceling of Narrow‐Band Signals in Seismic Data.” In SEG Technical Program Expanded Abstracts 1988. Society of Exploration Geophysicists.
     [Google Scholar]
  17. Guo, Q.1988. “Tie Design of 50 Hz Notch Filter and Its Effect.” Oil Geophysics Prospecting23, no. 5: 626–629. http://www.ogp‐cn.com.cn/CN/Y1988/V23/I5/626.
     [Google Scholar]
  18. Hu, B.2005. “Research on Industrial Frequency Interference Cancellation Method Based on Partial Coherence Analysis.” Master's thesis, Harbin Engineering University.
  19. Hu, W., and X.Lu. 2005. “The Improvement of Cosine Approach Method and Its Application to Remove Industrial Noise in Seismic Data.” Geophysical and Geochemical Exploration29, no. 6: 537–540. https://www.wutanyuhuatan.com/CN/Y2005/V29/I6/537#AbstractTab.
     [Google Scholar]
  20. Karsli, H., and D.Dondurur. 2018. “A Mean‐Based Filter to Remove Power Line Harmonic Noise From Seismic Reflection Data.” Journal of Applied Geophysics152: 1–10. https://doi.org/10.1016/j.jappgeo.2018.04.014.
     [Google Scholar]
  21. Li, G., and Q.Huang. 2007. “Getting Disturbing Industrial Frequency on the Principle of Cross‐Correlation With Software of LabView.” Microcomputer Information23, no. 1: 300–301.
     [Google Scholar]
  22. Li, W., Y.Niu, and M.Wu. 2001. “A New Method for Seismic Data Processing of Eliminating 50 Hz Disturbing Wave.” Petroleum Geology and Oilfield Development in Daqing20, no. 5: 67–68.
     [Google Scholar]
  23. Lichman, E., and E. J.Northwood. 1997. “High‐Resolution Velocity Notch Filter Without Gibbs Effect.” Geophysics62: 274–287. https://doi.org/10.1190/1.1444128.
     [Google Scholar]
  24. Ling, Y., and X.Guo. 1992. “Method for Suppressing the Non‐Surface Consistent Noises.” Oil Geophysics Prospecting27, no. 1: 13–28. http://www.ogp‐cn.com.cn/CN/Y1992/V27/I1/13.
     [Google Scholar]
  25. Linville, A. F., and R. A.Meek. 1992. “Cancaling Stationary Sinusoidal Noise.” Geophysics57: 1493–1501. https://doi.org/10.1190/1.1443216.
     [Google Scholar]
  26. Liu, Y.2003. “Extraction and Removal of Strong Power Interference.” Geophysical Prospecting for Petroleum42, no. 2: 154–159. https://www.geophysics.cn/CN/Y2003/V42/I2/154.
     [Google Scholar]
  27. Luo, G., S.Gao, G.Wei, and S.Wang. 2009. “Suppression of Mono‐Frequency Interference on Seismic Record by Chirp‐Z Transform Spectrum Analysis.” Oil Geophysics Prospecting44, no. 2: 166–172. http://www.ogp‐cn.com.cn/CN/Y2009/V44/I2/166.
     [Google Scholar]
  28. Meunier, J., and T.Bianchi. 2002. “Harmonic Noise Reduction Opens the Way for Array Size Reduction in VibroseisTM Operations.” In Proceedings of the SEG International Exposition and Annual Meeting. SEG.
  29. Nyman, D. C., and J. E.Gaiser. 1983. “Adaptive Rejection of High‐Line Contamination.” In Proceedings of the SEG Technical Program Expanded Abstracts 1983. Society of Exploration Geophysicists.
  30. Saucier, A., M.Marchant, and M.Chouteau. 2006. “Cancelling Stationary Sinusoidal Noise.” Geophysics71: V7–V18. https://doi.org/10.1190/1.2159063.
     [Google Scholar]
  31. Shoshitaishvili, E., L. S.Sorenson, and R. A.Johnson. 2001. “Data Improvement by Subtraction of High‐Amplitude Harmonics From the 2D Land Vertical‐ and Multi‐Component Seismic Data Acquired Over the Cheyenne Belt in SE Wyoming.” In Proceedings of the SEG Technical Program Expanded Abstracts 2001. Society of Exploration Geophysicists. https://doi.org/10.1190/1.1816540.
  32. Wang, B., and B.Di. 1985. “Narrow Band Auto‐Track Notch Filter.” Oil Geophysics Prospecting20, no. 4: 411–414. http://www.ogp‐cn.com.cn/CN/Y1985/V20/I4/411.
     [Google Scholar]
  33. Wang, T., X.Yu, M.Liu, H.Hu, and X.Zhou. 2010. “The Attenuation of Power Interference Based on S‐Transform.” Geophysical and Geochemical Exploration34, no. 4: 532–535. https://www.wutanyuhuatan.com/CN/Y2010/V34/I4/532.
     [Google Scholar]
  34. Widrow, B., J. R.Glover, J. M.McCool, et al. 1975. “Adaptive Noise Cancelling: Principles and Applications.” Proceedings of the IEEE63: 1692–1716. https://doi.org/10.1109/PROC.1975.10036.
     [Google Scholar]
  35. Wu, X., X.Li, M.Kong, H.Feng, and H.Zhou. 2003. “Harmonic Estimation and Removal Based on Independent Component Analysis.” Transactions of China Electrotechnical Society18, no. 4: 56–60. https://doi.org/10.19595/j.cnki.1000‐6753.tces.2003.04.012.
     [Google Scholar]
  36. Xia, H.2005. “Elimination of 50 Hz Power Interference via Wavelet Packet Transform and Sine Function Simulation.” Progress in Exploration Geophysics28, no. 5: 341–344. https://d.wanfangdata.com.cn/periodical/ktdqwljz200505008.
     [Google Scholar]
  37. Yu, Z., R.Abma, J.Etgen, and C.Sullivan. 2017. “Attenuation of Noise and Simultaneous Source Interference Using Wavelet Denoising.” Geophysics82: V179–V190. https://doi.org/10.1190/geo2016‐0240.1.
     [Google Scholar]
  38. Yuan, Y., S.Zhou, Y.Wang, and J.Gao. 2021. “Effective Frequency Estimation Method for Sinusoidal Interference in Seismic Data.” Geophysics86: V269–V284. https://doi.org/10.1190/geo2020‐0072.1.
     [Google Scholar]
/content/journals/10.1111/1365-2478.70120
Loading
Time‐Domain‐Normalized Cross‐Correlation Denoising Method for Single‐Frequency Interference in Seismic Data
Geophysical Prospecting 74, e70120 (2026); https://doi.org/10.1111/1365-2478.70120
/content/journals/10.1111/1365-2478.70120
/content/journals/10.1111/1365-2478.70120
Loading

Data & Media loading...

  • Article Type: Research Article
Keyword(s): coefficient R; cross‐correlation; normalization; single‐frequency interference; time domain

Most Cited This Month Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error