High-Resolution Volcanic Tremor Localization via MLE-Based Iterative Peeling Interferometry

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ID: 331580
2026
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Abstract
Summary Accurate source localization is critical for monitoring volcanic tremors, microseismic events, and earthquakes. Compared to other source localization algorithms, waveform-based interferometric imaging exhibits superior robustness. It proves particularly effective when confronting weak signal phase signatures, noise interference, and inaccurate velocity models. Despite shared methodological commonalities, high-resolution imaging and localization of volcanic tremors prove notably more challenging than other passive seismic tasks. This difficulty primarily arises from sparse monitoring networks, complex wavefield interactions with the subsurface, and the indistinct phase signatures inherent in tremor signals. Consequently, waveform-based interferometric imaging tends to suffer from more severe blurring effects (i.e., poorer spatial resolution) when applied to volcanic tremor localization and compared against other application fields. To address these resolution limitations, we propose a maximum likelihood estimation (MLE)-based iterative peeling interferometric imaging method. This approach synergizes the inherent noise robustness of interferometry with a rigorous iterative framework designed to deblur the source image. By constructing data-driven empirical wavelets and employing an adaptive whitening filter dynamically updated via the Sherman-Morrison formula, the method sequentially strips source responses from the residual wavefield. This adaptive procedure directly counters the energy smearing caused by sparse arrays, effectively suppressing sidelobe interference to achieve a highly focused source resolution. Synthetic tests based on the Katla scenario demonstrate that the proposed method yields significantly higher spatial resolution than existing techniques. Furthermore, it exhibits robust performance even under adverse array geometries, concurrent multi-source interference, and velocity model inaccuracies. Field application to the 2011 Katla data further validates this by recovering source locations consistent with known ice cauldrons.
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Authors Cheng Zhang, L. Azevedo, Yaru Xue, João Narciso, Zonghu Liao
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Journal geophysical journal international
Year 2026
DOI
10.1093/gji/ggag400
URL
https://doi.org/10.1093/gji/ggag400
Keywords Keywords not found

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