Identification of faults in the subsurface of Java Island using the ambient noise tomography method

Authors

  • Tio Azhar Prakoso Setiadi Research Center for Limnology and Water Resources, National Research and Innovation Agency, Bogor, Indonesia
  • Edy Hartulistiyoso Department of Mechanical and Biosystems Engineering, IPB University, Bogor, Indonesia
  • Muhammad Nur Aidi Department of Statistics and Data Science, IPB University, Bogor, Indonesia
  • Agustya Adi Martha Research Center for Limnology and Water Resources, National Research and Innovation Agency, Bogor, Indonesia
  • Yunus Daud Faculty of Mathematics and Natural Sciences Universitas Indonesia (UI), Depok 16424, Indonesia
  • Nova Heryandoko Agency for Meteorology, Climatology, and Geophysics (BMKG), Jakarta 10610, Indonesia
  • Yusuf Hadi Perdana Agency for Meteorology, Climatology, and Geophysics (BMKG), Jakarta 10610, Indonesia

DOI:

https://doi.org/10.54302/mausam.v76i2.6195

Keywords:

Java, Fault Identification, Ambient Noise Tomography, Rayleigh Wave, Cross-Correlation

Abstract

This study applies the Ambient Noise Tomography (ANT) method to identify faults in the subsurface seismic structure of Java Island, characterized by complex tectonic conditions. The research utilizes waveform data recorded in 2021 by 99 BMKG stationary seismic sensors distributed across Java Island. Data processing includes single data preparation, cross-correlation, stacking, dispersion curve measurement, group velocity tomography, and result interpretation. The inversion process generates tomographic images of Rayleigh wave group velocities ranging from  1.88 km/s to 2.60 km/s, revealing significant contrasts in velocity anomalies. These contrasts, located at the boundaries between low and high velocity zones, are strongly correlated with fault lines and volcanic zones across the island. The results demonstrate the capability of the ANT method to delineate subsurface geological structures, including active fault systems, with high precision.

Downloads

Published

01-04-2025

How to Cite

[1]
T. A. P. . Setiadi, “Identification of faults in the subsurface of Java Island using the ambient noise tomography method”, MAUSAM, vol. 76, no. 2, pp. 619–628, Apr. 2025.

Issue

Vol. 76 No. 2 (2025): MAUSAM

Section

Research Papers

License

Copyright (c) 2025 MAUSAM

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

All articles published by MAUSAM are licensed under the Creative Commons Attribution 4.0 International License. This permits anyone.

Anyone is free:

  • To Share - to copy, distribute and transmit the work
  • To Remix - to adapt the work.

Under the following conditions:

  • Share - copy and redistribute the material in any medium or format
  • Adapt - remix, transform, and build upon the material for any purpose, even
    commercially.