Comprehensive study of the volcanic seismicity of the Klyuchevskoy volcano group

• Main Author: Galina, Nataliya
• Other Authors: Institut des Sciences de la Terre (ISTerre), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB Université de Savoie Université de Chambéry )-Centre National de la Recherche Scientifique (CNRS)-Université Gustave Eiffel-Université Grenoble Alpes (UGA), Université Grenoble Alpes 2020-., Nikolai M. Shapiro
• Format: Doctoral or Postdoctoral Thesis
• Language: English
• Published: HAL CCSD 2023
• Subjects: Machine learning; Long-Period seismicity; Volcano monitoring; Source inversion; Apprentissage machine; Sismicité longue période; Surveillance d'activité volcanique; Inversion de source; [SDU.STU]Sciences of the Universe [physics]/Earth Sciences; Kamchatka
• Online Access: https://theses.hal.science/tel-04352286; https://theses.hal.science/tel-04352286/document; https://theses.hal.science/tel-04352286/file/GALINA_2023_archivage.pdf

Nowadays there are various tools and techniques to monitor volcanoes in order topredict their unrest and eruptions. One of the most effective approaches is based on in-terpretation of seismic observations. Volcanoes are very dynamic systems hosting a wholevariety of processes reflected in diverse seismic signals recorded by seismic stations. Anal-ysis and interpretation of these signals is the principal task of seismo-volcanic monitoring.This work is aimed at investigating the seismicity within the Klyuchevskoy volcanogroup (KVG) in Kamchatka. The KVG is one of the world’s largest and most activesubduction zone volcanic clusters whose aboundant seismo-volcanic activity make it agreat “natural laboratory” to study and advance volcano seismology.In the first part, we study in details the deep long period (DLP) earthquakes thatsystematically occur near the crust-mantle boundary beneath the Klyuchevskoy volcano.This seismicity is believed to be one of the earliest manifestation of the volcanic unrest.However, the source mechanism of the DLP earthquakes remains poorly understood. Tostart with, the statistical analysis of DLP events was performed. This investigation wasdone using a detailed catalog obtained after processing almost two years of continuousdata with the sensitive template matching algorithm. At the next step, we tried toreconstruct the source of DLP earthquakes using comparison of S-to-P waves amplitudesratios instead the full waveform or polarity inversions. As the main result of the first part,it was shown that the source mechanism of the DLP seismicity is different from the oneof tectonic earthquakes. Also, the obtained observations turned out to be in agreementwith previously reported connection of the deep magmatic reservoir of the KVG with itsactive volcanoes.Second part of this thesis is dealing with methods of automatic signal analysis based onMachine Learning (ML) algorithms of classification and clustering. The ML explorationwas started with the problem of separating two general classes of ...