Suppression of surface waves in seismic data using an adaptive time–frequency–wavenumber filter

Abstract

Surface waves are a prevalent form of coherent interference in seismic recordings, characterized by low frequency, high energy, and slow velocity, which can significantly affect seismic data processing. Currently, surface wave suppression is primarily achieved by leveraging the differences between surface waves and signal waves in the frequency, amplitude, and wavenumber domains. Among these methods, frequency–wavenumber (FK) filtering is widely used. However, it requires manual selection of regions during filtering, which becomes challenging when processing large volumes of seismic data. Therefore, adaptive surface-wave suppression methods are essential for practical data processing. FK filtering transforms data into the FK domain to suppress linear noise. However, because surface waves are dispersive and exhibit partial nonlinearity, FK filtering alone is insufficient to fully suppress them. To address these issues, this study introduces a temporal dimension into the FK domain, leading to the development of the time–frequency–wavenumber (TFK) transformation. This transformation further separates surface and signal waves in the time domain, thereby mitigating dispersion. Moreover, it facilitates adaptive filtering of seismic data across different time intervals in the FK domain. By cross-correlating FK data from different time periods, adaptive filters were derived for each interval, which were then applied to obtain filtered seismic records. Comparisons between synthetic and real-world data demonstrated that our approach effectively suppresses surface waves while preserving the relative amplitude characteristics of signal waves.

Keywords

Seismic noise suppression / Surface-wave suppression / Frequency dispersion / Frequency–wavenumber filter / Adaptive time–frequency–wavenumber filtering / Cross-correlation

Funding

This research was supported by the Open Fund of the SINOPEC Key Laboratory of Geophysics (Grant No. 36750000-24-FW0399-0004), the Natural Science Foundation of Xinjiang Uygur Autonomous Region (Grant No. 2022D01C659) under the “Tianchi Talent” Introduction Program, and the Open Fund of Northwest Oilfield Branch Company, SINOPEC (Grant No. 34400000-25-ZC0607-0156).

Conflict of interest

The authors declare they have no competing interests.

Author contributions

Conceptualization: Yong Wang Formal analysis: Yong Wang, Xuejie Gao Investigation: Xuejie Gao, Zerun Nian, Lang Yang Methodology: Yong Wang, Youjuan He, Zhili Chen Writing–original draft: Xuejie Gao Writing–review & editing: Youjuan He

Availability of data

Data associated with this research are available and can be obtained by contacting the corresponding author.

References

[1] Zheng JJ , Yin XY , Zhang GZ , Wu GH , Zhang ZS. The surface wave suppression using the second generation curvelet transform. Appl Geophys. 2010; 7(4): 325-335. doi: 10.1007/s11770—010—0257—x

[2] Wang D , Li Z , Huang J , Dong L , Ding C. Surface wave suppression based on the characteristic of reflected wave. In: Proceedings of Beijing 2014 International Geophysical Conference & Exposition; 21—24 April 2014; Beijing, China. Society of Exploration Geophysicists and Chinese Petroleum Society; 2014: 307-310. doi: 10.1190/igcbeijing2014—079

[3] Lv S , Gong X , Hu B , Xu Z , Zhang J , Cheng Q. Adaptive non—subsampled shearlet transform and its application to surface wave suppression. IEEE Trans Geosci Remote Sens. 2024; 62: 1-15. doi: 10.1109/TGRS.2024.3477954

[4] Li Q , Shen A , Guo Y , Wu J , Shi Y. Review of evaluating asphalt pavement structure integrity and strength with Rayleigh wave methods: techniques, applications, and trends. Measurement. 2024; 234: 114849. doi: 10.1016/j.measurement.2024.114849

[5] Tokeshi J , Karkee CK , Sugimura Y. Reliability of Rayleigh wave dispersion curve obtained from f—k spectral analysis of microtremor array measurement. Soil Dyn Earthq Eng. 2006; 26(2—4): 163-174. doi: 10.1016/j.soildyn.2005.02.013

[6] Kong XL , Chen H , Hu ZQ , Kang JX , Xu TJ , Li LM. Surface wave attenuation based on polarization attributes in time—frequency domain for multicomponent seismic data. Appl Geophys. 2018; 15(1): 99-110. doi: 10.1007/s11770—018—0656—y

[7] Rasol MA , Pérez—Gracia V , Fernandes FM , Pais JC , Santos—Assunçao S , Santos C , Sossa VG. GPR laboratory tests and numerical models to characterize cracks in cement concrete specimens exemplifying damage in rigid pavement. Measurement. 2020; 158: 107662. doi: 10.1016/j.measurement.2020.107662

[8] Meng A , Xu H , Feng X , Tan Y. Feasibility of freeze—thaw damage analysis for asphalt mixtures through dynamic nondestructive testing. Constr Build Mater. 2020; 233: 117220. doi: 10.1016/j.conbuildmat.2019.117220

[9] Wang X , Huang H , Shen S , Jin G , Mao Q , Lu H. Characterization of in situ modulus of asphalt pavement and its relation to cracking performance using SASW method. J Transp Eng Part B Pavements. 2020; 146(3): 04020039. doi: 10.1061/JPEODX.0000195

[10] Yuanyuan H , Rui Y , Jishun P , Xin L . A 3D surface wave attenuation method based on dispersion curve analysis and its application. Acta Geophys. 2024; 72(6): 4123-4138. doi: 10.1007/s11600—024—01318—2

[11] Serdyukov AS , Yablokov AV , Duchkov AA , Azarov AA , Baranov VD. Slant f—k transform of multichannel seismic surface wave data. Geophysics. 2019; 84(1): A19-A24. doi: 10.1190/geo2018—0430.1

[12] Serdyukov AS. Ground—roll extraction using the Karhunen—Loeve transform in the time—frequency domain. Geophysics. 2022; 87(2): A19-A24. doi: 10.1190/geo2021—0453.1

[13] Zheng Y , He DK , Feng X. Surface wave suppressing and decomposition using deep neural networks. In: Proceedings of 83rd EAGE Annual Conference & Exhibition; 6—9 Jun 2022; Madrid, Spain. European Association of Geoscientists & Engineers; 2022: 1-5. doi: 10.3997/2214—4609.202210218

[14] Jin Z , Li G , Ou G. Improvement of inverse dispersion technique for ground roll attenuation in sedimentary environment. J Appl Geophys. 2024; 220: 105268. doi: 10.1016/j.jappgeo.2023.105268

[15] Liu S , Birnie C , Bakulin A , Dawood A , Silvestrov I , Alkhalifah T. A self—supervised scheme for ground roll suppression. Geophys Prospect. 2024; 72(7): 2580-2598. doi: 10.1111/1365—2478.13522

[16] Son YH , Park H , Cho Y , Min DJ. Ground—roll attenuation using dual—model self—supervised selective learning with blind horizontal convolutional neural networks. J Appl Geophys. 2024; 224: 105363. doi: 10.1016/j.jappgeo.2024.105363

[17] Yablokov AV , Moiseev MV , Serdyukov AS , Litvichenko DA. Algorithm for surface wave suppression on 2D seismic data using the slant Karhunen—Loeve transform in a time—frequency domain. Russ Geol Geophys. 2024; 65(5): 650-662. doi: 10.2113/RGG20234660

[18] He XL , Liu SQ , Tong ZQ. 3—D denoising method through visual speed in frequency—wavenumber domain. J China Univ Pet (Nat Sci Ed). 2010(4): 62-66. [In Chinese]. doi: 10.3969/j.issn.1673—5005.2010.04.011

[19] Tian Y , Wang X , Peng G , Wang X , Su Q. Noise attenuation technology on wide azimuth seismic data. Oil Geophys Prospect . 2013; 48(2): 187-191. [In Chinese]. doi: 10.13810/j.cnki.issn.1000—7210.2013.02.013

[20] Askari R , Siahkoohi HR. Ground roll attenuation using the S and x—f—k transforms. Geophys Prospect. 2008; 56(1): 105-114. doi: 10.1111/j.1365—2478.2007.00659.x

[21] Liu Y , Fomel S. Seismic data analysis using local time—frequency decomposition. Geophys Prospect. 2013; 61(3): 516-525. doi: 10.1111/j.1365—2478.2012.01062.x

[22] Wang C , Wang Y. Ground roll attenuation using polarization analysis in the t—f—k domain. Geophys J Int. 2017; 210(1): 240-254. doi: 10.1093/gji/ggx152

[23] Wu Y , Pan S , Yi S , Chen J , Cui Q , Song G. An automatic screening method for the passive surface—wave imaging based on the F—K domain energy characteristics. IEEE Trans Geosci Remote Sens. 2023; 61: 1-12. doi: 10.1109/TGRS.2023.3321786

[24] Sun H , Liu E , Zhang F , Wang W , Li X. Seismic shear wave noise suppression and application to well tie. J Geophys Eng. 2024; 21(6): 1619-1635. doi: 10.1093/jge/gxae091

[25] Stockwell RG , Mansinha L , Lowe RP. Localization of the complex spectrum: the S transform. IEEE Trans Signal Process. 1996; 44(4): 998-1001. doi: 10.1109/78.492555

[26] Xu S , Zhang Y , Lambaré G. Antileakage Fourier transform for seismic data regularization in higher dimensions. Geophysics. 2010; 75(6): WB113-WB120. doi: 10.1190/1.3507248.