Vol 49, No 4 (2024)

Geoacoustic emission is the process of elastic wave generation by rocks as the result of dynamic reconstruction of their structure. Observation results show that mechanic processes, occurring in the source of a preparing earthquake, affect the geoacoustic emission dynamics. Modeling of geoacoustic emission zones, the regions of the earth crust surface with deformations of the order 10^-8 – 10^-5, has been earlier carried out to prove the relation between geoacoustic emission variations and the process of earthquake preparation. Results of the modeling, which was performed earlier, show that the level of calculated deformations at observation sites exceeds the tidal ones but differs by one order from the recorded deformations. This may be associated with the fact that the earth crust was considered as a homogeneous environment. In reality, the earth crust consists of rock layers, some part of which has supercritical state and manifests plastic and quasi-plastic properties. The present paper is devoted to the modeling of the earth crust inhomogeneities impact on spatial distribution of geoacoustic emission zones. Inhomogeneities are described by simple force system distributed over spherical inclusion surface. Intensity of the force action was assumed to be constant. Solutions for the boundary problem of elasticity linear theory were obtained in the form of Green’s functions convolution for homogeneous isotropic elastic half-space. Computational experiments were carried out, and lines of the field component levels of the displacement vectors of the earth crust surface were constructed. It was shown that spherical inclusions affect displacement vector field of the earth crust surface. The impact character depends on the number of inhomogeneous inclusions and their locations relative to the source of a preparing earthquake.

The paper proposes a generalization of the previously obtained mathematical model of geoacoustic emission, according to which the model takes into account the effects of heredity in dissipative terms. The model is a system of two coupled linear oscillators with non-constant coefficients and with fractional derivatives of Gerasimov-Caputo orders, which describe viscous friction (fractional friction). The mathematical model is studied numerically using a non-local explicit finite-difference scheme of the first order of accuracy, which was implemented in the Maple 2022 computer symbolic mathematics environment. In this computer environment, the modeling results were visualized: oscillograms and phase trajectories were constructed for different values of the model parameters. The interpretation of the modeling results is given. It is shown that fractional friction can affect the process of interaction of geoacoustic emission sources.

The study of the geodynamics problem is often carried out on the basis of spectral models, when the fields are fully or partially expanded in eigenfields (eigenmodes) of suitable spectral problems. The most meaningful from the physical point of view are spectral problems of free oscillations or free decay of fields. The compilation of spectral models first of all requires calculating the parameters of the basic modes, and then the model coefficients. Most often, these are the Galerkin coefficients. Then the problem of actually solving the model equations numerically arises. The paper describes a software package developed by the authors that allows solving such problems. It includes modules for calculating the mode parameters, a module for calculating the Galerkin coefficients, two modules for numerically solving the system, and a noise generation module. The package allows calculating the model with hereditary quenching of the α-effect by the field energy. Two types of the quenching functional kernel are provided, requiring different difference schemes. These schemes are implemented in two numerical solution modules. Random noise simulates the effect of spontaneous synchronization of small-scale field components, which is absent on average. The calculation of the parameters of the basic modes and Galerkin coefficients is performed using combined symbolic-numerical computations, so the corresponding modules are implemented in the Maple package. The need for symbolic computations is associated with the great complexity of the expressions of the modes themselves and the integrands when calculating the Galerkin coefficients. Therefore, the task arises first of all to form the necessary expressions. This is done using symbolic calculations. The remaining modules are implemented in C++. The developed package can be useful for specialists studying the geodynamo problem based on spectral models and memory effects in this problem.

The paper proposes an algorithm for identifying the trace of an artificial whistling atmospheric signal (whistle) in a spectrogram, implemented in Python in the PyCharm 2024.1 integrated development environment. The algorithm allows you to identify the whistler trace by setting a certain threshold value (filter). The filter takes into account the signal intensity in the spectrum, the standard deviation of values from the mean, and a certain multiplier that allows you to exclude noise and identify only the most significant peaks in the signal. In the algorithm, using a mask based on the filter, it is possible to obtain an array of frequencies for the trace of an artificial whistler. The computer program allows you to save the resulting array in a text file, which can be used for further analysis in various spreadsheet processors, as well as build whistler trace graphs for visual research. The article tested the adequacy of the algorithm using the example of calculating the dispersion coefficient. It was shown that the algorithm gives good results.

The paper proposes a method for improvement of the quality of geophysical data preparation on the example of geoacoustic observations to train neural networks when solving the problem of identification of pre- and post-seismic anomalies. The method is based on the transformation of geoacoustic emission signal associated with deformation processes in near-surface rocks into three-dimensional images. A series of such images contains the information on signal characteristics dynamics. Thee-dimensional images are the matrices consisting of the the distribution vectors of selected characteristics (spectral, structural, statistical and so on). The structure, data tensor, is formed from a series of such images. It is supplied to the neural network input. Due to external factors impact (weather, industrial), a recorded geoacoustic signal is distorted. Thus, it is necessary to clean the initial data. In order to do this, we suggest using a neural network which clusters the prepared images and removes outliers in the obtained clusters. A new tensor is formed from the remaining images. It undergoes the cleaning procedure again. This process continues until no outliers are observed in the output data as the result of clustering. When the cleaning is over, the second neural network will be trained to identify common features and differences, as well as hidden patterns in the geoacoustic pulse flux. Application of the developed method for tensor cleaning, based on artificial intelligence technologies, allows us to improve significantly the quality of data preparation. The obtained results will be useful for the investigations in the fields of identification and classification of pre- and post-seismic anomalies in geoacoutstic emission signals associated with deformation processes in near-surface rocks in a seismically active region.

The paper describes an ionospheric component of “Aurora” interactive system. The “Aurora” system implements new methods of data analysis based on the combination of modern means of digital signal processing with classical methods of data analysis. The paper presents the results of the ionospheric component based on a generalized multicomponent model of ionospheric parameters developed by the authors. The model and numerical algorithms based on it make it possible to study the ionospheric parameter dynamics during disturbed periods (to detect anomalous periods and estimate their parameters) in detail. The ionospheric component of “Aurora” system performs processing and analysis of the foF2 ionospheric critical frequency parameters recorded at Paratunka station (Kamchatka Territory) and forms a conclusion on the state of the ionosphere above Kamchatka. This development was carried out by a team of the system analysis laboratory of IKIR FEB RAS. The paper presents numerical algorithms implemented in the system and system results during increased geomagnetic activity (as an example of a weak magnetic storm from June 15, 2024) and seismic processes in Kamchatka (as an example of the November 2, 2018 earthquake). During the periods of the considered events, anomalous changes were detected in the ionosphere, which were accompanied with both the increase and decrease of the electron concentration.

The process of rock stress-strain state change causes acoustic radiation, which is called rock acoustic emission or geoacoustic emission. The relation between the earthquake preparation process and rock acoustic emission variations, which are called pre-seismic anomalies, has been stated in a number of investigations. The general mechanism of occurrences of these anomalies is associated with the fact that formation of a preparing earthquake source causes changes in the stress-strain state of rocks, surrounding it. One of the kinds of anomalies, occurring at the final stage of earthquake preparation, is the appearance of clearly expressed direction of acoustic activity. The main hypothesis of occurrence of this phenomenon is that a preparing earthquake source impact causes formation of constant direction of principle stress axes at an observation point. In their turn, the direction of these axes determines the primary orientation of acoustic radiation sources. To confirm this hypothesis, axis orientations of the main stresses, determined by the earthquake preparation process, were modeled. The estimates are based on the model constructed within the framework of elasticity linear theory where the Earth crust is considered in the form a homogeneous isotropic elastic half-space and the force impact at a preparing earthquake source is considered in the form of a combination of forces double pairs. Elastic deformation potential energy, accumulated during the earthquake preparation process, is taken into account. In the paper, we used the data from the catalog of earthquake source mechanics «The Global Centroid-Moment-Tensor Catalog» on seismic events occurred near Kamchatka peninsula from 1976 until 2020. As long as the acoustic radiation direction depends on the azimuthal direction to earthquake epicenter, all the considered seismic events were divided into three groups by the method of -averages according to spatial locations of their epicenters. The modeling results were compared with experimental estimates of the main stress axis directions at Mikizha observation site (52.99^° N, 158.22^° E). The estimates were earlier obtained based on the geoacoustic emission directivity anomalies. It was shown that histograms of main stress axis direction distributions agree with the results of estimates for two groups of earthquakes. Modal intervals of distribution histograms fall within the range of experimental estimates from 290^° to 320^° and from 20^° to 50^° accordingly.

Anomalous changes in the parameters characterizing the state of the ionospheric E and F regions observed before the onset of seismic events can be considered as possible ionospheric precursors of these earthquakes. In order to identify seismoionospheric disturbances preceding the onset of earthquakes, the work used hourly values of the h′Es, hmF2, fbEs, fbEs and foF2 parameters, which were obtained for the period 2016–2023 at the ionospheric station of vertical radio sounding located in the village of Paratunka (52.97^◦ N, 158.24^◦ E). Deviations of the values of the ionospheric parameter complex from the upper limit of the range of their background values during the daily interval in the absence of geomagnetic disturbances were considered as a possible ionospheric precursor of earthquakes. The methods of A.A. Gusev, G.M. Molchan, the Hansen-Kuiper criterion, and the reliability and validity of the precursor were used to estimate the prognostic efficiency. The prognostic efficiency was estimated for earthquakes that occurred in the time interval 2016-2023, with magnitudes M ≥ 5.0,M ≥ 5.5, M ≥ 6.0, hypocenter depths of up to 100 km and epicentral distances of up to 400 km to the location of the ionospheric station. According to the obtained estimates of the prognostic efficiency of the complex of ionospheric parameters under consideration, the forecast of seismic events with magnitudes M≥5.0 and M≥5.5 differs from random guessing and, therefore, the identified ionospheric disturbances can be associated with the processes of earthquake preparation. The highest values of the forecast efficiency were obtained for earthquakes with magnitudes M≥ 5.5.