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A Probabilistic Tremor Location Method
Author(s) -
Li Ka Lok,
Gudmundsson Olafur
Publication year - 2020
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1029/2019gl085538
Subject(s) - seismometer , robustness (evolution) , probabilistic logic , computer science , geology , bayes' theorem , algorithm , geodesy , data mining , statistics , bayesian probability , seismology , mathematics , artificial intelligence , biochemistry , chemistry , gene
A method to locate tremor with an unclear onset is introduced. The method maps envelopes of cross‐correlated records from pairs of seismographs to signal likelihoods using Bayes' theorem. The likelihood time series are then back projected to obtain likelihoods of source location in space. Assuming that information derived from different station pairs is independent, the joint likelihood for all station pairs is the product of all individual station pair likelihoods. Its peak and spread give the most probable source location and its uncertainty. Robustness of the method has been evaluated with synthetic tests. The method recovers true location within 0.5 km with realistic noise characteristics in synthetic data. Uncertainty estimates are consistent with location deviations for sources inside the seismic network. When applied to real data from Katla and Eyjafjallajökull volcanoes in southern Iceland, their likely tremor source is also recovered within 1 km.