AccScience Publishing / AJWEP / Online First / DOI: 10.36922/AJWEP026330222
Cite this article
1
Download
61
Views
Related Info Links
More by Authors Links
Journal Browser
Volume | Year
Issue
Search
News and Announcements
View All
ORIGINAL RESEARCH ARTICLE

Active–passive multichannel analysis of surface waves integration for reconnaissance-scale characterization of shallow limestone bedrock in northern Vietnam

Nguyen Nhat Kim Ngan1,2* ,  Nguyen Xuan Kha2,3 ,  Nguyen Thanh Hai4,5
Show Less
1 Faculty of Physics and Engineering Physics, University of Science, Ho Chi Minh , Vietnam
2 Vietnam National University, Ho Chi Minh City , Vietnam
3 Faculty of Geology and Petroleum Engineering, University of Technology, Ho Chi Minh , Vietnam
4 Institute of Earth Sciences, Ho Chi Minh City , Vietnam
5 Viet Nam Academy of Science and Technology, Ha Noi , Vietnam
Received: 10 August 2026 | Revised: 3 September 2026 | Accepted: 3 September 2026 | Published online: 10 October 2026
© 2026 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
Abstract

Reliable bedrock-depth information is essential for foundation design and seismic site characterization, yet borehole-only investigations provide sparse coverage and active-source surface-wave surveys may lack the low-frequency energy needed to resolve deeper interfaces. This study evaluates co-located active and roadside-passive multichannel analysis of surface waves at three sites in Quang Hanh Ward, Quang Ninh Province, northern Vietnam. Twenty-four 4.5 Hz geophones were deployed at 3 m spacing; active records were generated with a 10 kg sledgehammer, and 32 s passive records were recorded using traffic noise. Normalized frequency-phase-velocity images were combined and inverted to preferred one-dimensional shear-wave velocity (VS) profiles. Depth-averaged velocities and successive 5 m velocity ratios were compared with two boreholes and Standard Penetration Test data. The combined dispersion information extended from approximately 3 Hz to site-dependent upper limits of about 15–20 Hz and was interpreted to a depth of 50 m. The preferred models show a low-velocity surficial unit (VS = 164–364 m/s) over a high-velocity unit assigned to fractured limestone (approximately 1,500–2,300 m/s). The principal transition occurs at 10–15 m at Site 1 and 15–20 m at Sites 2 and 3, overlapping borehole evidence that places limestone at approximately 14–16 m. VS30 values of 513, 591, and 451 m/s place all three sites in Site Class C under the American Society of Civil Engineers 7-22/International Building Code 2024 and Ground Type B under Eurocode 8. The field example indicates that active–passive integration can extend usable bandwidth while retaining shallow resolution. Because only three lines and two non-blind boreholes were available and inversion uncertainty was not quantified, the proposed velocity-ratio minimum should be treated as a site-specific screening indicator rather than a generally validated bedrock estimator.

Keywords
Active–passive multichannel analysis of surface waves
Shear-wave velocity
Limestone bedrock
Dispersion inversion
Borehole validation
Funding
This research was funded by Vietnam National University Ho Chi Minh City (VNU-HCM) under a project (grant number CB2025-18-11) within the framework of the program titled “Strengthening the capacity for education and basic scientific research integrated with strategic technologies at VNU-HCM, aiming to achieve advanced standards comparable to regional and global levels during the 2025–2030 period, with a vision toward 2045.”
Conflict of interest
The authors declare they have no competing interests.
References
  1. Kundu P, Raman D, Pain A, Das J, Sundaram R, Gupta S. Seismic site characterization and development of SPT(N) to shear wave velocity correlation of Noida city. Sci Rep. 2025;15(1):12368. doi: 10.1038/s41598-025-94502-3
  2. Thakur H, Anbazhagan P. Geology, geomorphology and Vs30 based site classification of the Himalayan region using a stacked model. Eng Geol. 2025;355:108229. doi: 10.1016/j.enggeo.2025.108229
  3. Park CB, Miller RD, Xia J. Multichannel analysis of surface waves. Geophysics. 1999;64(3):800-808. doi: 10.1190/1.1444590
  4. Albesher ZI, Alotaibi A, Aljabbab A. Identifying subsurface weak zones in Riyadh, Saudi Arabia, using multichannel analysis of surface wave technique. J King Saud Univ Sci. 2025;37:4562025. doi: 10.25259/jksus_456_2025
  5. Kuang X, Pan Y, Zhang Z, Yuan S. Automatic picking of multimodal Rayleigh-wave dispersion curves from multicomponent data with an energy-density-based clustering method. Geophys J Int. 2025;243(1):ggaf323. doi: 10.1093/gji/ggaf323
  6. Yang XH, Han P, Zhuang J, et al. Identification of higher-mode numbers in dispersion curves for Rayleigh wave inversion. IEEE Trans Geosci Remote Sens. 2025;63:1-13. doi: 10.1109/tgrs.2025.3589016
  7. Sgattoni G, Morelli C, Lattanzi G, et al. Geophysical investigation and 3D modeling of bedrock morphology in an urban sediment-filled basin: the case of Bolzano (Northern Italy). Pure Appl Geophys. 2024;181(6):1871-1893. doi: 10.1007/s00024-024-03512-1
  8. Nguyen NNK, Le CVA, Vu TM, et al. Determination of shear wave velocity using multichannel analysis of surface wave in M’Drak District, Dak Lak Province, Vietnam. IEEJ Trans Electr Electron Eng. 2025;20(11):1896-1900. doi: 10.1002/tee.70089
  9. Chang YH, Tsai CC, Ge L, Park D. Novel method to estimate horizontal variability of shear wave velocity through multichannel analysis of surface waves. Eng Geol. 2024;343:107799. doi: 10.1016/j.enggeo.2024.107799
  10. Ólafsdóttir EÁ, Bessason B, Erlingsson S, Kaynia AM. A tool for processing and inversion of MASW data and a study of inter-session variability of MASW. Geotech Test J. 2024;47(5):1006-1025. doi: 10.1520/gtj20230380
  11. Park CB, Miller RD, Ryden N, Xia J, Ivanov J. Combined use of active and passive surface waves. J Environ Eng Geophys. 2005;10(3):323-334. doi: 10.2113/JEEG10.3.323
  12. Park CB, Miller RD. Roadside passive multichannel analysis of surface waves (MASW). J Environ Eng Geophys. 2008;13(1):1-11. doi: 10.2113/JEEG13.1.1
  13. Cheng F, Xia J, Luo Y, et al. Multichannel analysis of passive surface waves based on crosscorrelations. Geophysics. 2016;81(5):EN57-EN66. doi: 10.1190/GEO2015-0505.1
  14. Baglari D, Dey A, Taipodia J. A state-of-the-art review of passive MASW survey for subsurface profiling. Innov Infrastruct Solut. 2018;3(1):66. doi: 10.1007/s41062-018-0171-2
  15. Dal Moro G. MASW? A critical perspective on problems and opportunities in surface-wave analysis from active and passive data (with few legal considerations). Phys Chem Earth. 2023;130:103369. doi: 10.1016/j.pce.2023.103369
  16. Aimar M, Foti S. Near-field effects on the in situ estimation of shear-wave velocity and damping ratio from MASW tests. J Geotech Geoenviron Eng. 2026;152(1):06025007. doi: 10.1061/jggefk.gteng-14297
  17. Adhikari R, Macciotta R, McClymont A, Farrugia J, Deisman N, Hughes S. Managing uncertainties in active MASW: a practical guide for geotechnical engineers. Geotech Geol Eng. 2025;43(7):381. doi: 10.1007/s10706-025-03342-5
  18. Zhao Y, Dutta U, Yang ZJ. Joint inversion of MASW and ambient noise HVSR data for estimating shear wave velocity in warm permafrost sites. Cold Reg Sci Technol. 2025;239:104623. doi: 10.1016/j.coldregions.2025.104623
  19. Ai H, Song X, Zhang X, et al. Transdimensional joint inversion of surface wave, refraction, and resistivity data using modified barnacles mating optimizer for near-surface investigations. J Appl Geophys. 2025;241:105863. doi: 10.1016/j.jappgeo.2025.105863
  20. Akın Ö, Sayıl N. Soil characterization in landslide-prone areas using ground shear strain based on active and passive source surface wave methods. Pure Appl Geophys. 2025;182(4):1579-1600. doi: 10.1007/s00024-025-03696-0
  21. Mukherjee S, Bhaumik M, Naskar T. Modified S-transform based high-resolution dispersion imaging method for multi-channel surface wave data. Soil Dyn Earthq Eng. 2025;192:109284. doi: 10.1016/j.soildyn.2025.109284
  22. Liu F, Deng B, Su R, Bai L, Ouyang W. DispFormer: a pretrained transformer incorporating physical constraints for dispersion curve inversion. J Geophys Res Mach Learn Comput. 2025;2(3):e2025JH000648. doi: 10.1029/2025jh000648
  23. Wang XH, Cao ZJ, Wu T, Du W, Li DQ. Probabilistic inversion of shear wave velocity profile based on the dispersion curve from multichannel analysis of surface waves and inequality constraints on layer thicknesses. Eng Geol. 2025;352:108063. doi: 10.1016/j.enggeo.2025.108063
  24. Berti S, Aleardi M, Stucchi E. A probabilistic full waveform inversion of surface waves. Geophys Prospect. 2024;72(9):3448-3473. doi: 10.1111/1365-2478.13595
  25. Aimar M, Foti S, Cox BR. Novel techniques for in situ estimation of shear-wave velocity and damping ratio through MASW testing – I: a beamforming procedure for extracting Rayleigh-wave phase velocity and phase attenuation. Geophys J Int. 2024;237(1):506-524. doi: 10.1093/gji/ggae051
  26. Vishwakarma P, Bora SS, Prashant A. Variability in receivers responses of MASW test on undulated grounds: a numerical perspective. J Appl Geophys. 2024;226:105410. doi: 10.1016/j.jappgeo.2024.105410
  27. Vishwakarma P, Bora SS, Prashant A. Analysis of shear wave velocity estimation using MASW on sloping grounds. Acta Geophys. 2024;73(1):359-378. doi: 10.1007/s11600-024-01382-8
  28. Hong Y, Xia J, Zhang H, et al. Azimuth correction for passive surface wave dispersion based on polarization analysis. Geophys J Int. 2024;238(3):1638-1650. doi: 10.1093/gji/ggae232
  29. Abbas HA, Al-Jeznawi D, Al-Janabi MAQ, Bernardo LFA, Jacinto MASC. Exploring shear wave velocity–NSPT correlations for geotechnical site characterization: a review. CivilEng. 2024;5(1):119-135. doi: 10.3390/civileng5010006
  30. Sambath M, Chandrasekaran SS, Maithani S, Ganapathy GP. Seismic site characterization of Coimbatore City, Tamil Nadu, India using the multi-channel analysis of surface waves (MASW) test and correlations between shear-wave velocity and SPT-N. J Appl Geophys. 2025;232:105575. doi: 10.1016/j.jappgeo.2024.105575
  31. Nguyen NNK. Deriving geotechnical parameters for foundation design in Ea Trang, Vietnam, through combined seismic methods. Econ Environ Geol. 2025;58(4):351-359. doi: 10.9719/EEG.2025.58.4.351
  32. Karslı H, Babacan AE, Akın Ö. Subsurface characterization by active and passive source geophysical methods after the 06 February 2023 earthquakes in Turkey. Nat Hazards. 2024;120(6):5257-5286. doi: 10.1007/s11069-024-06422-6
  33. Abdelbaset M, Mohamed A, Sawires R, Omran AAA, Thabet M. Passive and active seismics to identify geotechnical site characterization at industrial zone, Aswan, Egypt. J Appl Geophys. 2025;243:105948. doi: 10.1016/j.jappgeo.2025.105948
  34. Philley PD, Taipodia J, Pana T, Anshu AK. Enhancing subsurface imaging: optimization of data acquisition and processing parameters in passive roadside MASW surveys. Disaster Adv. 2024;17(10):54-65. doi: 10.25303/1710da054065
  35. Moon SW, Hayashi K, Ku T. Estimating spatial variations in bedrock depth and weathering degree in decomposed granite from surface waves. J Geotech Geoenviron Eng. 2017;143(7):04017020. doi: 10.1061/(ASCE)GT.1943-5606.0001679
  36. Yang XH, Zhou Y, Han P, Feng X, Chen X. Near-surface Rayleigh wave dispersion curve inversion algorithms: a comprehensive comparison. Surv Geophys. 2024;45(3):773-818. doi: 10.1007/s10712-024-09826-y
  37. Anshu AK, Taipodia J, Kumar SS, Dey A. Seismic site classification of Itanagar city, India, considering spatial variation of shear wave velocity obtained using extensive active MASW survey. J Appl Geophys. 2025;243:105981. doi: 10.1016/j.jappgeo.2025.105981
  38. Mazanec M, Valenta J, Málek J. Does VS30 reflect seismic amplification? Observations from the West Bohemia Seismic Network. Nat Hazards. 2024;120(13):12181-12202. doi: 10.1007/s11069-024-06679-x
  39. Shi Z, Wang C. Joint inversion of ERT and ambient noise surface wave data with DPC-guided fuzzy c-means clustering for near-surface imaging. Geophys J Int. 2024;238(3):1334-1352. doi: 10.1093/gji/ggae227
  40. International Code Council. 2024 International Building Code. Washington (DC): International Code Council; 2023. https://codes.iccsafe.org/content/IBC2024V2.0
  41. European Committee for Standardization. Eurocode 8: Design of Structures for Earthquake Resistance—Part 1: General Rules, Seismic Actions and Rules for Buildings. EN 1998-1:2004. European Committee for Standardization; 2004. Accessed August 10, 2026. https://eurocodes.jrc.ec.europa.eu/EN-Eurocodes/eurocode-8-design-structures-earthquake-resistance
  42. Abdelrahman K. Shear wave velocity structure at King Saud University, Saudi Arabia, derived from MASW and microtremor arrays. Sci Rep. 2025;15(1):11497. doi: 10.1038/s41598-025-90894-4
  43. Vantassel JP, Cox BR, Hubbard PG, Yust M. Extracting high-resolution, multi-mode surface wave dispersion data from distributed acoustic sensing measurements using the multichannel analysis of surface waves. J Appl Geophys. 2022;205:104776. doi: 10.1016/j.jappgeo.2022.104776
  44. Vishwakarma P, Prashant A. Hard sandwiched soil layer detection using higher mode in active MASW test. Geotech Geol Eng. 2024;42(7):5519-5538. doi: 10.1007/s10706-024-02843-z
Share
Back to top
Asian Journal of Water, Environment and Pollution, Electronic ISSN: 1875-8568 Print ISSN: 0972-9860, Published by AccScience Publishing