Automated earthquake detection and high-resolution catalog construction in the Jailolo volcanic region, Indonesia

Siti Navisa; Titi Anggono; Firman Syaifuddin; Agnis Triahadini; Surya Putra Ade

doi:10.15625/2615-9783/24522

Author affiliations

Authors

Siti Navisa Geophysical Engineering, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia
Titi Anggono Research Center for Geological Disaster of the National Research and Innovation Agency, Tangerang, Indonesia
Firman Syaifuddin Geophysical Engineering, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia
Agnis Triahadini Geophysical Engineering, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia
Ade Surya Putra Research Center for Geological Disaster of the National Research and Innovation Agency, Tangerang, Indonesia

DOI:

https://doi.org/10.15625/2615-9783/24522

Keywords:

Jailolo, EQTransformer, GaMMA, NonLinLoc, HypoDD

Abstract

The Jailolo region, located on Halmahera Island, is characterized by intense seismic activity due to its proximity to two subduction zones and the Halmahera volcanic arc. To optimize the analysis of local earthquake activity in the region, we used an automated workflow that combines the deep-learning phase picker EQtransformer with the unsupervised machine learning association algorithm GaMMA to construct a high-resolution microseismic catalog. Phase arrivals were first identified using the EQTransformer and subsequently associated with each other using GaMMA, a Bayesian Gaussian Mixture Model with spatial clustering for earthquake event detection. This workflow produced 6,174 preliminary detections, of which 2,902 high-quality events were retained after relocation and filtering. The earthquakes predominantly occurred at depths shallower than 50 km, with an average local magnitude (M_L) of 0.91. The obtained catalog revealed a large number of previously unreported small-magnitude earthquakes in the International Seismological Center (ISC) catalog. The completeness magnitude (Mc = 0.63) indicates a significant improvement in detection capability, enabling detailed analysis of microseismicity. The study highlights the effectiveness of automated machine-learning techniques in improving the resolution of seismicity patterns in a tectonically complex region such as Jailolo.

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References

Ammon C.J., Velasco A.A., Lay T., Wallace T.C., 2021. Earthquake size & descriptive earthquake statistics. In C.J. Ammon, A.A. Velasco T. Lay, T.C. Wallace (Ed.), Foundations of Modern Global Seismology (Second Edition). Academic Press, 197–222. https://doi.org/10.1016/B978-0-12-815679-7.00014-8.

Apandi T., Sudana D., 1980. Peta geologi lembar Ternate, Maluku Utara. Geological Research and Development Centre, Bandung, Indonesia, 9.

Badan Meteorologi, Klimatologi, dan Geofisika (BMKG), 2017. Siaran pers gempabumi swarm di Jailolo Prov. Maluku Utara, 29 September 2017 [Press release on earthquake swarm in Jailolo, North Maluku]. Pusat Gempa Nasional. https://www.bmkg.go.id/siaran-pers/siaran-pers-gempabumi-swarm-di-jailolo-prov-maluku-utara (accessed 8 September 2025).

Beyreuther M., Barsch R., Krischer L., Megies T., Behr Y., Wassermann J., 2010. ObsPy: A Python Toolbox for Seismology. Seismological Research Letters, 81(3), 530–533. https://doi.org/10.1785/gssrl.81.3.530.

Ghosh A., Newman A., Thomas A., Farmer G., 2008. Interface locking along the subduction megathrust from b-value mapping near Nicoya Peninsula, Costa Rica. Geophysical Research Letters, 35(1), L01301. https://doi.org/10.1029/2007GL031617.

Gunawan E., Ghozalba F., Syauqi, Widiastomo Y., Meilano I., Hanifa N.R., Daryono Hidayati S., 2016. Field Investigation of the November to December 2015 Earthquake Swarm in West Halmahera, Indonesia. Geotechnical and Geological Engineering, 35(1), 425–432. https://doi.org/10.1007/s10706-016-0117-4.

Jiang C., Zhang P., White M.C.A., Pickle R., Miller M.S., 2022. A Detailed Earthquake Catalog for Banda Arc-Australian Plate Collision Zone Using Machine-Learning Phase Picker and an Automated Workflow, The Seismic Record, 2(1), 1–10. https://doi.org/10.1785/0320210041.

Kagan Y.Y., 2010. Earthquake size distribution: Power-law with exponent?. In Y. Y. Kagan (Ed.), Tectonophysics, Elsevier, 490(1–2), 103–114. https://doi.org/10.1016/j.tecto.2010.04.034.

Kennett B.L.N., Engdahl E.R., Buland R., 1995. Constraints on seismic velocities in the Earth from travel times. Geophysical Journal International, 122(1), 108–124. https://doi.org/10.1111/j.1365-246X.1995.tb03540.x.

Kubo H., Naoi M., Kano M, 2024. Recent advances in earthquake seismology using machine learning. Earth, Planets and Space, 76(1), 36. https://doi.org/10.1186/s40623-024-01982-0.

Lomax A., Curtis A., 2001. Fast, probabilistic earthquake location in 3D models using oct-tree importance sampling. Geophys. Res. Abstr., 3(955), 10–1007.

Macpherson C.G., Hall R., 2002. Timing and tectonic controls in the evolving orogen of SE Asia and the western Pacific and some implications for ore generation. In C. G. Macpherson & R. Hall (Eds.), Geological Society, London, Special Publications. Geological Society of London, 204(1), 49–67. https://doi.org/10.1144/GSL.SP.2002.204.01.04.

McBrearty I.W., Beroza G.C., 2023. Earthquake phase association with graph neural networks. Bulletin of the Seismological Society of America, 113(2), 524–547. https://doi.org/10.1785/0120220182.

Mignan A., 2014. The debate on the prognostic value of earthquake foreshocks: a meta-analysis. Scientific Reports, 4, 4099. https://doi.org/10.1038/srep04099.

Morris J.D., Jezek P.A., Hart S.R., Hill J.B., 1983. The Halmahera Island Arc, Molucca Sea collision zone, Indonesia: A geochemical survey. The Tectonic and Geologic Evolution of Southeast Asian Seas and Islands: Part 2. Geophysical Monograph Series, 27, 373–387. https://doi.org/10.1029/GM027p0373.

Mousavi S.M., Ellsworth W.L., Zhu W., Chuang L.Y., Beroza G.C., 2020. Earthquake transformer an attentive deep-learning model for simultaneous earthquake detection and phase picking. Nature Communications, 11(1), 3952. https://doi.org/10.1038/s41467-020-17591-w.

Nanjo K.Z., Schorlemmer D., Woessner J., Wiemer S., Giardini D., 2010. Earthquake detection capability of the Swiss Seismic Network. Geophysical Journal International, 181(3), 1713–1724. https://doi.org/10.1111/j.1365-246X.2010.04593.x.

Naoi M., Nakatani M., Otsuki K., et al., 2015. Steady activity of microfractures on geological faults loaded by mining stress. Tectonophysics, 649, 100–114. https://doi.org/10.1016/j.tecto.2015.02.025.

Nguyen C.N., Van D.N., Thi G.H., Le M.N., Huang B.S., Tien H.N., Le Quang K., Huu H.N., 2022. Automatic earthquake detection and phase picking in Muong Te, Lai Chau region: an application of machine learning in observational seismology in Vietnam. Vietnam Journal of Earth Sciences, 44(3), 430–446. https://doi.org/10.15625/2615-9783/17253.

Nishikawa T., Ide S., 2014. Earthquake size distribution in subduction zones linked to slab buoyancy. Nature Geoscience, 7(12), 904–908. https://doi.org/10.1038/ngeo2279.

Nugraha A.D., Supendi P., Widiyantoro S., Daryono, Wiyono S., 2018. Hypocenter relocation of earthquake swarm around Jailolo volcano, North Molucca, Indonesia using the BMKG network data: time periods of September 27-October 10, 2017. In AIP conference proceedings. AIP Publishing LLC, 1987(1), 020093. https://doi.org/10.1063/1.5047378.

Passarelli L., Heryandoko N., Cesca S., Rivalta E., Rasmid, Rohadi S., Dahm T., Milkereit C., 2018. Magmatic or Not Magmatic? The 2015–2016 Seismic Swarm at the Long-Dormant Jailolo Volcano, West Halmahera, Indonesia. Frontiers in Earth Science, 6, 79. https://doi.org/10.3389/feart.2018.00079.

Passarelli L., Heryandoko N., Muzli, Rasmid, Zimmer M., Cesca S., Rivalta E., Rohadi S., Merdianto U., Dahm T., Milkereit C., 2016. Jailolo network, West Halmahera - Indonesia 2016/2018 [Data set]. GFZ Data Services. https://doi.org/10.14470/2T7561654577.

Pita-Slim O., Chamberlain C.J., Townend J., Warren-Smith E., 2023. Parametric testing of EQTransformer's performance against a high-quality, manually picked catalog for reliable and accurate seismic phase picking. The Seismic Record, 3(4), 332–341. https://doi.org/10.1785/0320230024.

Rachman G., 2023. Tomografi Seismik Waktu Tempuh Untuk Penentuan Struktur 3-D Vp, Vs, Dan Rasio Vp/Vs Di Zona Tumbukan Laut Maluku Dan Implikasinya Terhadap Aktivitas Tektonik Dan Gunungapi Di Halmahera (Disertasi Doktoral, Institut Teknologi Sepuluh Nopember).

Richter C.F., 1935. An Instrumental Earthquake Magnitude Scale. Bulletin of the Seismological Society of America, 25, 1–32.

Shearer P.M., 1999. Introduction to Seismology. Cambridge University Press, Cambridge.

Tamaribuchi K., Kudo S., Shimojo K., Hirose F., 2023. Detection of hidden earthquakes after the 2011 Tohoku earthquake by automatic hypocenter determination combined with machine learning. Earth, Planets and Space, 75(1), 155. https://doi.org/10.1186/s40623-023-01915-3.

Waldhauser F., 2001. HypoDD-A program to compute double-difference hypocenter locations. U.S. Geological Survey Open-File Report 2001-113. https://doi.org/10.3133/ofr01113.

Waldhauser, F., 2000, A Double-Difference Earthquake Location Algorithm: Method and Application to the Northern Hayward Fault, California: Bulletin of the Seismological Society of America, 90, 1353–1368. Doi: 10.1785/0120000006.

White M.C.A., Ben‐Zion Y., Vernon F.L., 2019. A Detailed Earthquake Catalog for the San Jacinto Fault‐Zone Region in Southern California: Journal of Geophysical Research: Solid Earth, 124, 6908–6930. Doi: 10.1029/2019JB017641.

Wiemer S., Wyss M., 2000. Minimum magnitude of completeness in earthquake catalogs: examples from Alaska, the Western United States, and Japan. Bulletin of the Seismological Society of America, 90(4), 859–869. https://doi.org/10.1785/0119990114.

Woollam J., Münchmeyer J., Tilmann F., Rietbrock A., Lange D., Bornstein T., Diehl T., Giunchi C., Haslinger F., Jozinović D., Michelini A.,

Saul J., Soto H., 2022. SeisBench-A toolbox for machine learning in seismology. Seismological Research Letters, 93(3), 1695–1709. https://doi.org/10.1785/0220210324.

Wulandari A., Anggraini A., Suryanto W., 2018, Hypocenter Analysis of Aftershocks Data of the Mw 6.3, 27 May 2006 Yogyakarta Earthquake Using Oct-Tree Importance Sampling Method: Applied Mechanics and Materials, 881, 89–97. Doi: 10.4028/www.scientific.net/AMM.881.89.

Zhang Q., Guo F., Zhao L., Wu Y., 2017. Geodynamics of divergent double subduction: 3-D numerical modeling of a Cenozoic example in the Molucca Sea region, Indonesia. Journal of Geophysical Research: Solid Earth, 122(5), 3977–3998. https://doi.org/10.1002/2017JB013991.

Zhong Y., Tan Y.J., 2024. Deep learning‐based phase picking for volcano tectonic and long‐period earthquakes. Geophysical Research Letters, 51(12), e2024GL108438. https://doi.org/10.1029/2024GL108438.

Zhu W., Hou A.B., Yang R., Datta A., Mousavi S.M., Ellsworth W.L., Beroza G.C., 2023. QuakeFlow: a scalable machine-learning-based earthquake monitoring workflow with cloud computing. Geophysical Journal International, 232(1), 684–693. https://doi.org/10.1093/gji/ggac355.

Zhu W., McBrearty I.W., Mousavi S.M., Ellsworth W.L., Beroza G.C., 2022. Earthquake phase association using a Bayesian Gaussian mixture model. Journal of Geophysical Research: Solid Earth, 127(5), e2021JB023249. https://doi.org/10.1029/2021JB023249.