IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v121y2025i14d10.1007_s11069-025-07462-2.html
   My bibliography  Save this article

A layered segmentation method for fault geometry reconstruction: integrating surface traces and aftershock sequence

Author

Listed:
  • Jingwei Li

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences
    China Earthquake Administration
    GFZ Helmholtz Centre for Geosciences, Telegrafenberg)

  • Zizhan Zhang

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Zhiguo Deng

    (GFZ Helmholtz Centre for Geosciences, Telegrafenberg)

  • Wei Zhan

    (China Earthquake Administration)

  • Yunguo Chen

    (East China Jiaotong University)

  • Wei Chen

    (China Earthquake Administration)

Abstract

Well-constrained fault geometry is crucial for understanding the fault-rupture process. However, uncertainties in non-linear inversion methods and spatial discrepancies between aftershock distributions and surface rupture traces pose challenges in resolving irregular fault geometry. In this study, we propose a novel Layered Segmentation Method (LSM), which integrates aftershock sequences and surface rupture traces to construct more reasonable fault geometry. The method segments aftershocks into discrete clusters and fits polylines to these clusters using the differential evolution algorithm, thereby overcoming limitations of conventional approaches. We validate the LSM using synthetic datasets for both high-angle strike-slip and low-angle dip-slip fault cases, demonstrating its ability to reliably reconstruct fault surfaces. In application to the 2021 Mw 7.4 Maduo and the 2022 Mw 6.7 Menyuan earthquakes, the LSM effectively reconciles the spatial discrepancies between aftershock sequences and surface ruptures, resulting in fault geometry that aligned well with observed aftershock distributions. Coseismic slip inversion based on these geometries shows that the predicted surface displacements and slip patterns are consistent with geodetic and geological observations. Compared to conventional methods, the LSM offers a more robust and physically grounded representation of fault geometry, highlighting its critical role in controlling coseismic stress and slip distributions.

Suggested Citation

  • Jingwei Li & Zizhan Zhang & Zhiguo Deng & Wei Zhan & Yunguo Chen & Wei Chen, 2025. "A layered segmentation method for fault geometry reconstruction: integrating surface traces and aftershock sequence," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 121(14), pages 17025-17043, August.
  • Handle: RePEc:spr:nathaz:v:121:y:2025:i:14:d:10.1007_s11069-025-07462-2
    DOI: 10.1007/s11069-025-07462-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11069-025-07462-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11069-025-07462-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Maryam Alghannam & Ruben Juanes, 2020. "Understanding rate effects in injection-induced earthquakes," Nature Communications, Nature, vol. 11(1), pages 1-6, December.
    2. Songlin Shi & Meng Wang & Yonatan Poles & Jay Fineberg, 2023. "How frictional slip evolves," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    3. Phoebe M. R. DeVries & Fernanda Viégas & Martin Wattenberg & Brendan J. Meade, 2018. "Deep learning of aftershock patterns following large earthquakes," Nature, Nature, vol. 560(7720), pages 632-634, August.
    4. Christopher H. Scholz, 1998. "Earthquakes and friction laws," Nature, Nature, vol. 391(6662), pages 37-42, January.
    5. Jaeseok Lee & Victor C. Tsai & Greg Hirth & Avigyan Chatterjee & Daniel T. Trugman, 2024. "Fault-network geometry influences earthquake frictional behaviour," Nature, Nature, vol. 631(8019), pages 106-110, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Nkomom, Théodule Nkoa & Okaly, Joseph Brizar & Mvogo, Alain, 2021. "Dynamics of modulated waves and localized energy in a Burridge and Knopoff model of earthquake with velocity-dependant and hydrodynamics friction forces," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 583(C).
    2. D.Sornette & J.V. Andersen & A. Helmstetter & S.Gluzman & J.R.Grasso & V. Pisarenko, 2003. "Slider-Block Friction Model for Landslides: Application to Vaiont and Laclapière Landslides," THEMA Working Papers 2003-33, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.
    3. Pelap, F.B. & Kagho, L.Y. & Fogang, C.F., 2016. "Chaotic behavior of earthquakes induced by a nonlinear magma up flow," Chaos, Solitons & Fractals, Elsevier, vol. 87(C), pages 71-83.
    4. Shoubiao Zhu, 2013. "Numerical simulation of dynamic mechanisms of the 2008 Wenchuan Ms8.0 earthquake: implications for earthquake prediction," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 69(2), pages 1261-1279, November.
    5. Yunping Bai & Yifu Xu & Shifan Chen & Xiaotian Zhu & Shuai Wang & Sirui Huang & Yuhang Song & Yixuan Zheng & Zhihui Liu & Sim Tan & Roberto Morandotti & Sai T. Chu & Brent E. Little & David J. Moss & , 2025. "TOPS-speed complex-valued convolutional accelerator for feature extraction and inference," Nature Communications, Nature, vol. 16(1), pages 1-13, December.
    6. Társilo Girona & Kyriaki Drymoni, 2024. "Abnormal low-magnitude seismicity preceding large-magnitude earthquakes," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    7. Xin Li & Jie Zhang & Rongxin Li & Qi Qi & Yundong Zheng & Cuinan Li & Ben Li & Changjun Wu & Tianyu Hong & Yao Wang & Xiaoxiao Du & Zaipeng Zhao & Xu Liu, 2021. "Numerical Simulation Research on Improvement Effect of Ultrasonic Waves on Seepage Characteristics of Coalbed Methane Reservoir," Energies, MDPI, vol. 14(15), pages 1-15, July.
    8. R. Tiwari & Ashutosh Chamoli, 2015. "Is tidal forcing critical to trigger large Sumatra earthquakes?," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 77(1), pages 65-74, May.
    9. Hassam Bin Waseem & Irfan Ahmad Rana, 2025. "A meta-review of disaster research," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 121(11), pages 12427-12460, June.
    10. Dongdong Chen & Zhiqiang Wang & Zaisheng Jiang & Shengrong Xie & Zijian Li & Qiucheng Ye & Jingkun Zhu, 2023. "Research on J 2 Evolution Law and Control under the Condition of Internal Pressure Relief in Surrounding Rock of Deep Roadway," Sustainability, MDPI, vol. 15(13), pages 1-22, June.
    11. Caishan Yan & Hsuan-Yi Chen & Pik-Yin Lai & Penger Tong, 2023. "Statistical laws of stick-slip friction at mesoscale," Nature Communications, Nature, vol. 14(1), pages 1-8, December.
    12. Kasyful Qaedi & Mardina Abdullah & Khairul Adib Yusof & Masashi Hayakawa & Nur Fatin Irdina Zulhamidi, 2025. "Multi-class classification automated machine learning for predicting earthquakes using global geomagnetic field data," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 121(12), pages 14531-14544, July.
    13. Matteo Picozzi & Antonio Giovanni Iaccarino, 2021. "Forecasting the Preparatory Phase of Induced Earthquakes by Recurrent Neural Network," Forecasting, MDPI, vol. 3(1), pages 1-20, January.
    14. Hongyu Sun & Matej Pec, 2021. "Nanometric flow and earthquake instability," Nature Communications, Nature, vol. 12(1), pages 1-9, December.
    15. Zhou, Yuhao & Wang, Yanwei, 2022. "An integrated framework based on deep learning algorithm for optimizing thermochemical production in heavy oil reservoirs," Energy, Elsevier, vol. 253(C).
    16. Elisenda Bakker & John Kaszuba & Sabine den Hartog & Suzanne Hangx, 2019. "Chemo‐mechanical behavior of clay‐rich fault gouges affected by CO2‐brine‐rock interactions," Greenhouse Gases: Science and Technology, Blackwell Publishing, vol. 9(1), pages 19-36, February.
    17. Qiyue Wang & Yekun Zhang & Jiaqi Zhang & Zekang Zhao & Xijun He, 2024. "On the use of VMD-LSTM neural network for approximate earthquake prediction," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 120(14), pages 13351-13367, November.
    18. Stuart Fraser & William Power & Xiaoming Wang & Laura Wallace & Christof Mueller & David Johnston, 2014. "Tsunami inundation in Napier, New Zealand, due to local earthquake sources," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 70(1), pages 415-445, January.
    19. Sandro Andrés & David Santillán & Juan Carlos Mosquera & Luis Cueto-Felgueroso, 2019. "Thermo-Poroelastic Analysis of Induced Seismicity at the Basel Enhanced Geothermal System," Sustainability, MDPI, vol. 11(24), pages 1-18, December.
    20. Wenjuan Sun & Paolo Bocchini & Brian D. Davison, 2020. "Applications of artificial intelligence for disaster management," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 103(3), pages 2631-2689, September.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:nathaz:v:121:y:2025:i:14:d:10.1007_s11069-025-07462-2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.