We present a method for automatic location of dominant sources of seismovolcanic tremor in 3‐D, based on the spatial coherence of the continuously recorded wavefield at a seismic network. We analyze ...4.5 years of records from the seismic network at the Klyuchevskoy volcanic group in Kamchatka, Russia, when four volcanoes experienced tremor episodes. After enhancing the tremor signal with spectral whitening, we compute the daily cross‐correlation functions related to the dominant tremor sources from the first eigenvector of the spectral covariance matrix and infer their daily positions in 3‐D. We apply our technique to the tremors beneath Shiveluch, Klyuchevskoy, Tolbachik, and Kizimen volcanoes and observe the yearlong preeruptive volcanic tremor beneath Klyuchevskoy from deep to shallow parts of the plumbing system. This observation of deep volcanic tremor sources demonstrates that the cross‐correlation‐based method is a very powerful tool for volcano monitoring.
Plain Language Summary
Volcanic tremors are the seismic signature of magmatic and hydrothermal fluids passing through volcanic conduits. Locating them in 3‐D is of real interest because it could allow us to monitor in more detail movements of magma inside volcanic edifices and, in some cases, to forecast eruptive episodes. The location of tremor in 3‐D nevertheless remains challenging because signals generated by tremors do not present any clear onset that could be used for picking arrival times and for determining source location. We design a method based on cross correlations that recovers the differential travel times between receivers of a seismic network from the analysis of the statistically dominating waves in the wavefield. We present an application of the proposed method to volcanoes in Kamchatka, Russia, and show that we can track the preeruptive tremor episode in depth before the main eruption of the Klyushevskoy volcano.
Key Points
A seismic network‐based method for the automatic 3‐D location of volcanic tremors is developed
The migration of deep volcanic tremor sources to the surface is tracked in time beneath Klyuchevskoy volcano
The developed location method is fully automatic and can be updated continuously with new data
This paper reports the results of seismic, electromagnetic, and gravity surveys, as well as seismicity data in the lithosphere at depth for the active volcanoes in the Avacha–Koryaksky group which is ...part of the East Kamchatka volcanic belt. We have developed an integrated geophysical model for the crust and lithospheric mantle in the area of study. The resulting distribution of crustal geophysical inhomogeneities, in particular, beneath Avacha Volcano, was used to study the main features of intracrustal fluid saturation and of pathways as channels for deeper fluids to rise to the upper crust. The integrated model assumes that the stresses that arise at boundaries of zones with different conditions of defluidization constitute one of the factors to produce seismicity beneath the active volcanoes. We also incorporate data from regional seismic tomography to deal with a general scheme for deep processes in the lithosphere and the system that supplies magma to the volcanoes. It is assumed that active volcanoes, in particular, Avacha, are connected to the asthenospheric layer of the lithosphere mantle at a depth of about 70–120 km, whence fluids/melts are coming into the magma chamber in the lower crust with subsequent formation of a peripheral chamber in the upper crust beneath the volcanic cone due to the heat supplied by the lower crustal source.
Continuous noise-based monitoring of seismic velocity changes provides insights into volcanic unrest, earthquake mechanisms and fluid injection in the subsurface. The standard monitoring approach ...relies on measuring traveltime changes of late coda arrivals between daily and reference noise cross-correlations, usually chosen as stacks of daily cross-correlations. The main assumption of this method is that the shape of the noise correlations does not change over time or, in other terms, that the ambient-noise sources are stationary through time. These conditions are not fulfilled when a strong episodic source of noise, such as a volcanic tremor, for example, perturbs the reconstructed Green's function. In this paper, we propose a general formulation for retrieving continuous time-series of noise-based seismic velocity changes without the requirement of any arbitrary reference cross-correlation function (CCF). Instead, we measure the changes between all possible pairs of daily cross-correlations and invert them using different smoothing parameters to obtain the final velocity change curve. We perform synthetic tests in order to establish a general framework for future applications of this technique. In particular, we study the reliability of velocity change measurements versus the stability of noise CCFs. We apply this approach to a complex data set of noise cross-correlations at Klyuchevskoy volcanic group (Kamchatka), hampered by loss of data and the presence of highly non-stationary seismic tremors.
—As part of the international collaboration of several research groups from Russia, France, and Germany, 77 temporary seismic stations were installed in the summer of 2015 for one-year period to ...conduct a detailed study of the deep structure of the Earth’s crust and upper mantle in the region of the Klyuchevskoi Volcano Group (KVG), Kamchatka Peninsula. One of the results of the KISS experiment (Klyuchevskoi Investigation –Seismic Structure of an extraordinary volcanic system) was the final catalog based on the joint data from the temporary stations and the permanent network of the Kamchatka Branch of the Geophysical Survey of the Russian Academy of Sciences (KB GS RAS). The catalog comprises 2136 events, including 560 for which the permanent network catalog lacked sufficient data for correct processing. The catalog in .xlsx format and the station bulletin in .isf format are presented in the supplementary material to the paper. A comparative analysis is performed of joint solutions of two catalogs, one obtained solely from the data of the KB GS RAS permanent network stations and another from a denser seismic network integrated with KISS stations.
We analyse daily cross-correlation computed from continuous records by permanent stations operating in vicinity of the Klyuchevskoy group of volcanoes (Kamchatka). Seismic waves generated by volcanic ...tremors are clearly seen on the cross-correlations between some pairs of stations as strong signals at frequencies between 0.2 and 2 Hz and with traveltimes typically shorter than those corresponding to interstation propagation. First, we develop a 2-D source-scanning algorithm based on summation of the envelops of cross-correlations to detect seismic tremors and to determine locations from which the strong seismic energy is continuously emitted. In an alternative approach, we explore the distinctive character of the cross-correlation waveforms corresponding to tremors emitted by different volcanoes and develop a phase-matching method for detecting volcanic tremors. Application of these methods allows us to detect and to distinguish tremors generated by the Klyuchevskoy and the Tolbachik, volcanoes and to monitor evolution of their intensity in time.
Seismological Observations in Kamchatka were significantly improved due to the installation of new telemetered seismic stations near active volcanoes and the implementation of modern digital ...technologies for data transmission, acquisition, and processing in 1996–1998. This qualitative leap forward made it possible, not only to create an effective system for monitoring Kamchatka volcanoes and for timely and reliable assessment of the state of these volcanoes, but also to draw conclusions about volcanic hazard. The experience that was gained allowed us to make successful short-term forecasts for eight moderate explosive eruptions on Bezymyannyi Volcano of the ten that have occurred in 2004–2010, successful intermediate-term forecasts of evolving activity on Klyuchevskoi Volcano in three cases, as well as providing a successful forecast of an explosive eruption on Kizimen Volcano.
A new approach is proposed for determining earthquake hypocenters aimed at a more comprehensive characterization of its uncertainty and ambiguity. Application of the new approach to study the seismic ...focal subduction zones and volcanic seismicity is discussed by the example of the data of the Kamchatka Branch of the Geophysical Survey of the Russian Academy of Sciences.
—Long-period earthquakes and tremors, on a par with volcano-tectonic earthquakes, are one of two main classes of volcano-seismic activity. It is believed that long-period volcanic seismicity is ...associated with pressure fluctuations in the magmatic and hydrothermal systems beneath volcanoes and can therefore be used as a precursor of the impending eruptions. At the same time, the physical mechanism of the long-period seismicity is still not fully understood. In this work, we have studied the long-period earthquakes that occur at the crust–mantle boundary beneath the Klyuchevskoi volcanic group in Kamchatka in order to establish their recurrence law—the relationship between the magnitude and frequency of occurrence of the events. In the region under study, the earthquakes pertaining to this type are most numerous and characterize the state of the deep magma reservoir located at the crust–mantle boundary. The changes in the seismic regime in this part of the magmatic system can be one of the early precursors of eruptions. For a more thorough characterization of the frequency–magnitude relationship of the discussed events, we compiled a new catalog of the deep long-period earthquakes based on the matched-filter processing of continuous seismograms recorded by the network stations of the Kamchatka Branch of the Geophysical Survey of the Russian Academy of Sciences in 2011–2012. For these earthquakes, we also used a magnitude determination method that provides the estimates close to the moment magnitude scale. The analysis of the obtained catalog containing more than 40 000 events shows that the frequency–magnitude relationships of the earthquakes markedly deviate from the Gutenberg–Richter power-law distribution, probably testifying to the seismicity mechanism and peculiarities of the sources that differ from the common tectonic earthquakes. It is shown that the magnitude distribution of the deep long-period earthquakes is, rather, described by the distributions with characteristic mean values such as the normal or gamma distribution.
Seismicity began to be recorded in October 2017 around the dormant Bolshaya Udina Volcano (B. Udina in what follows) situated 10 km southeast of Plosky Tolbachik Volcano. Seismic tomography showed ...the existence of a long-lived magma chamber south of B. Udina in the area of the Tolud River. The chamber has its top at a depth of about 15 km, and may probably be connected to the Plosky Tolbachik plumbing system (Koulakov et al., 2017). Saltykov et al. (2018) and Koulakov et al. (2019) related the observed resumption of seismic activity to a hypothetical emplacement of magma beneath the Udina volcanoes, pointing out a high likelihood of the resumption of volcanic activity. The present study examines data from permanent seismic stations showing a systematic displacement of the center of seismic energy southward from B. Udina from October 2017 through August 2019. The center characterizes the location of the volume that generates the bulk of seismicity. We used images of the Sentinel-1A satellite (wavelength 5.6 cm) taken from a descending orbit of track 60 during the period from June 7, 2017 through September 23, 2017 (10 images) and during the period from May 21, 2018 to September 30, 2018 (12 images) to determine time series and average velocities of displacement on the slopes of B. Udina. Persistent scatterers could only be identified at the foot of B. Udina. An analysis of displacement time series for the surface of the volcano showed that the character of displacements in 2017 and 2018 on the southwestern and eastern slopes remained nearly the same, while the average rate of displacement on the northwestern slope decreased in 2018. We used three images of the ALOS-2 PALSAR-2 satellite (wavelength 23.5 cm) taken on October 4, 2016, June 13, 2016, and October 2, 2018 from an ascending orbit to construct paired interferograms, which characterize displacements for the time period between images. The displacements on both interferograms did not exceed a few centimeters, except for narrow zones confined to local relief forms. The deformations thus detected were most likely due to surface processes. The deformed volumes related to pressure changes in the magma chamber at a depth of 5 km must have linear dimensions of 10–15 km, while the displacement areas detected in the satellite images are considerably smaller. These results suggested an alternative model that postulates the resumption of seismic activity to accompany the retreat and sinking of magma melt from B. Udina into the chamber in the Tolud R. area as identified by tomographic techniques.
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