Bezymianny Volcano is one of the most active volcanoes in the world. In 1955, for the first time in history, Bezymianny started to erupt and after six months produced a catastrophic eruption with a total volume of eruptive products of more than 3 km3. Following explosive eruption, a lava dome began to grow in the resulting caldera. Lava dome growth continued intermittently for the next 57 years and continues today. During this extended period of lava dome growth, 44 Vulcanian-type strong explosive eruptions occurred between 1965 and 2012. This paper presents a summary of activity at Bezymianny Volcano from 1956 to 2010 with a focus on descriptive details for each event.

Nineteen Holocene eruptive centers (cinder cones with lava flows and maars) were located and described in the Avacha horst and anticline zone west of the East Kamchatka volcanic area. A tephrochronological study and the carbon-14 dating of soil and plant remains ranked the eruptive centers into three age groups: 11 000-7700, 3000-2500, and 1200-600 carbon-14 years B. P. The eruptive centers of these groups are believed to have been operating roughly synchronously with the periods of active magma injection in the East Kamchatka volcanic area. Eruptive histories were reconstructed for some of the volcanic centers. The structural and tectonic settings, geographical positions, and elevations of the centers were analyzed. The volume (1.1 km3) and weight (1.8 X 10^9 metric tons) of the erupted rocks were evaluated. The productivity of the plateau basalt volcanism was found to be 10-100 times lower than the plateau basalt productivity in the area of grabens and synclines, possibly, because of the more shallow basement in the horsts and because of the fact that the compression of the crust under uplifting conditions hampered the magma rise toward the surface. Most of the lavas and pyroclastics are basalts of the medium-potassic series, some having medium (54-62) and some elevated (65-70) Kmg values.

Currently, video observation systems are actively used for volcano activity monitoring. Video cameras allow us to remotely assess the state of a dangerous natural object and to detect thermal anomalies if technical capabilities are available. However, continuous use of visible band cameras instead of special tools (for example, thermal cameras), produces large number of images, that require the application of special algorithms both for preliminary filtering out the images with area of interest hidden due to weather or illumination conditions, and for volcano activity detection. Existing algorithms use preselected regions of interest in the frame for analysis. This region could be changed occasionally to observe events in a specific area of the volcano. It is a problem to set it in advance and keep it up to date, especially for an observation network with multiple cameras. The accumulated perennial archives of images with documented eruptions allow us to use modern deep learning technologies for whole frame analysis to solve the specified task. The article presents the development of algorithms to classify volcano images produced by video observation systems. The focus is on developing the algorithms to create a labelled dataset from an unstructured archive using existing and authors proposed techniques. The developed solution was tested using the archive of the video observation system for the volcanoes of Kamchatka, in particular the observation data for the Klyuchevskoy volcano. The tests show the high efficiency of the use of convolutional neural networks in volcano image classification, and the accuracy of classification achieved 91%. The resulting dataset consisting of 15,000 images and labelled in three classes of scenes is the first dataset of this kind of Kamchatka volcanoes. It can be used to develop systems for monitoring other stratovolcanoes that occupy most of the video frame.

The Paratunsky and Verkhne-Paratunsky fields (Kamchatka, Russia) are examples of low-temperature nitrogen (LT N2) geothermal systems that are widespread throughout the world and are believed to have formed as a result of penetration of meteoric water into deep faults and heat mining from host rocks under background heat flow and temperature gradient conditions. However, no one has tested the geologically long-term thermal recharge capability of such systems to be recharged by heat and water under real 3D environmental conditions. A solution to this unsolved problem has been obtained here using specific examples. The two closely spaced reservoirs are 15 km apart, composed of volcanogenic rocks of Eocene-Quaternary age and characterized by shallow permeability reservoirs underlain by extinct volcanic conductive roots, where 60–90 ◦C thermal N2 SO4–Na waters circulate. The Paratunsky reservoir has a 60-year history of intensive exploitation (150–250 kg/s), while the Verkhne-Paratunsky reservoir is just being brought into development. Application of a simple radial-cylindrical (RZ) model to the Verkhne-Paratunsky geothermal system allowed us to show the principal possibility of formation of a circulating hydrothermal system in a structure with a radius of about 15 km and a circulation depth of -3 km within the first thousand years at a temperature of 60 ◦C and a flow rate of 60 kg/s.
Then a three-dimensional numerical (3D) model of the Verkhne- Paratunsky and Paratunsky low-temperature nitrogen geothermal system was constructed, assuming that the upper part of the pre-Cretaceous basement is a permeable conduit surface and the roots of extinct volcanoes provide vertical down-flow recharge and up-flow discharge of this natural heat and mass circulation system. This numerical model covers all significant thermal discharge features, recharge area of the adjacent highlands. Subsequent modeling confirms the possibility of increasing the temperature to 80 ◦C, diluting the initially brine-saturated NaCl permeable reservoirs and maintaining up-flow rate at observed values for thousands of years from the onset of hydrothermal circulation.