Journal of the Earthquake Engineering Society of Korea (한국지진공학회논문집)

Earthquake Engineering Society of Korea (한국지진공학회)
권호 표지
DOI QR코드

DOI QR Code

Study on the Ground-Motion Acceleration Conversion Methods from the horizontal Strain-Rate Array Data of Distributed Acoustic Sensing

수평방향 분산진동센서 변형률 자료의 지반가속도 변환 방법에 대한 연구

  • Yun, Kwan-Hee (Safety Laboratory, Korea Electric Power Corporation (KEPCO) Research Institute) ;
  • Choi, Seunghun (Research Institute of Energy and Resources, Seoul National University) ;
  • Yoon, Byoungjoon (Geological Storage Research Center, Korea Institute of Geoscience and Mineral Resources)
  • 연관희 (한전전력공사 전력연구원 안전연구소 ) ;
  • 최승훈 (서울대학교 에너지자원신기술연구소) ;
  • 윤병준 (한국지질자원연구원 탄소저장연구센터)
  • Received : 2026.03.03
  • Accepted : 2026.04.10
  • Published : 2026.05.01
Download PDF
⟨ Previous Next ⟩

Abstract

This study evaluates ground-motion (GM) acceleration conversion methods by applying them to strain-rate data from a horizontal Distributed Acoustic Sensing (DAS) array under both idealized and real-world conditions. We test four conversion methods-1) slant-stacking, 2) Lior's method, 3) Lindsey's method, and 4) Curvelet transform-through numerical modeling and by applying them to a publicly available 9 km horizontal DAS array dataset. Numerical simulations reveal critical calculation factors specific to each method and show that numerically derived apparent ground velocity can deviate from theoretical values when multiple elastic waves arrive simultaneously. In real-world applications, the slant-stacking and Lior's methods are relatively insensitive to the measurement length of the straight DAS array. By contrast, the Curvelet method exhibits strong sensitivity to this factor, whereas Lindsey's method shows weaker dependence. Implementing Lior's method in the frequency-wavenumber domain also requires pre-determining water-levels by comparing adjacent seismograms. Additionally, we find that Lior's method generates excessively high spectral levels above 13 Hz, which may lead to underestimation of the high-frequency spectral attenuation parameter (κ0), a key parameter in GM simulation. Collectively, these findings provide a technical guideline for the use of horizontal DAS arrays in future observational earthquake seismology.

Keywords

References

  1. Lior I, Sladen A, Mercerat D, Ampuero JP, Rivet D, Sambolian S. Strain to ground motion conversion of distributed acoustic sensing data for earthquake magnitude and stress drop determination. Solid Earth. 2021;12:1421-1442. https://doi.org/10.5194/se-12-1421-2021
  2. Lior I. Earthquake source parameter estimation using Distributed Acoustic Sensing and frequency wavenumber scaling. Bull Seismol Soc Am. 2025;115(3):1267-1278. https://doi.org/10.1785/0120240117
  3. Lindsey NJ, Rademacher H, Ajo-Franklin JB. On the broadband instrument response of fiber-optic DAS arrays. J Geophys Res Solid Earth. 2020;125(2):e2019JB018145. https://doi.org/10.1029/2019JB018145
  4. Atterholt J, Zhan Z, Shen Z, Li Z. A unified wavefield-partitioning approach for distributed acoustic sensing. Geophys J Int. 2021;228(2):1410-1418. https://doi.org/10.1093/gji/ggab407
  5. Zhai Q, Yin J, Yang Y, Atterholt JW, Li J, Husker A, Zhan Z. Comprehensive evaluation of DAS amplitude and its implications for earthquake early warning and seismic interferometry. J Geophys Res Solid Earth. 2025;130(1):e2024JB030288. https://doi.org/10.1029/2024JB030288
  6. Ben-Zeev S, Lior I. Physics-based earthquake early warning using distributed acoustic sensing. Sci Rep. 2026;16. Available from: https://doi.org/10.1038/s41598-025-32269-3
  7. Yun KH, Choi SK, Lee KR, Song SY. Case study of detecting earthquakes using long-range(＞30 km) underground fiber-optic Distributed Acoustic Sensing (in Korean). Proceeding of EESK Conference 2022. 2022 Mar;25.
  8. Yun KH, Choi SK, Lee KR. Acquisition of DVS data using dark-fiber of underground power cable and comparative analysis with seismic sensors (TR.71FL.C2025.0081, in Korean). Korea Electric Power Corporation Research Institute; c2025 Apr. 72 p.
  9. Choi S. Vehicle-Induced DAS Signal Simulation with Arbitrary 3D Fiber Geometries: An Integrated Quasi-Static and Dynamic Framework [Master's thesis]. Seoul: Seoul National University; c2026.
  10. Nazarian S, Stokoe KH. In Situ Determination of Elastic Moduli of Pavement Systems by Spectral-Analysis-of-Surface-Waves Method: Theoretical Aspects. Federal Highway Administration; c1986.
  11. Candès E, Demanet L, Donoho D, Ying L. Fast Discrete curvelet transforms. Multiscale Model Simul. 2006;5(3):861-899. https://doi.org/10.1137/05064182X
  12. Atterholt J. atterholt/DAS-unit-conversion: DAS Unit Conversion Code [Internet]. Zenodo; 2025 [cited 2026 Mar 11]. Available from: https://github.com/atterholt/DAS-unit-conversion
  13. Anderson JG, Hough SE. A model for the shape of the Fourier amplitude spectrum of acceleration at high frequencies. Bull Seismol Soc Am. 1984;74(5):1969-1993.