Vol 25, No 3 (2025)

Variational-combinatoric approach is used when solving linear and nonlinear inverse problems of geophysics within the framework of discrete potential. The acquired data about physical fields and their sources are of discrete character. Combinatoric methods of discrete mathematics allow us to organize some selective choice of the information on the physical field elements. Analytical approximations are built only by means of verified data which can be recognized as useful signal, not as an arbitrary or systematic noise.

The spatial structure of polar auroras is described by the fractal dimension of glow fluctuations and its anisotropy from direction. The fractal dimension is estimated from the slope in the logarithmic axes of the spectrum in the range of 1.5–50 km, obtained through discrete wavelet transformation of the intensity fluctuation of the glow using Daubechies wavelets of order 5. The variability of the structures is characterized by the slope of the anisotropy variation spectrum over time. The statistics of these characteristics are presented according to the data of the ground-based all-sky camera of the Polar Geophysical Institute in Apatity for 2013–2020 and referenced to the position inside the auroral oval and the values of the geomagnetic field at Lovozero observatory. An algorithm for modeling the structure of polar auroras based on these characteristics is discussed.

The relevance of the work is determined by the automation of monitoring processes of natural and technical systems, not so much in terms of their measurement component, but in terms of interpreting monitoring results in terms of the properties of the desired object. In this work, these are submerged pipeline systems – main oil and gas pipelines, as a special case of geotechnical objects. The goal of developing an automated workstation (AWS) for a specific object is the ultimate parameterization of the interpretation procedure and the unification of the final graphical constructions within the framework of a single digital image of main pipelines. Taking into account the deterministic type of geotechnical object and the objectives of the survey, research methods include, in addition to non-destructive magnetometric testing as a method of obtaining primary data: methods of qualitative and quantitative interpretation of multi-channel magnetometry materials; methods of systematics and graphical display of primary data and the results of their interpretation. Within the framework of approaches generally accepted in the oil and gas industry, the digital image of damaged pipeline sections is based on ideas about the thinning of pipe walls and the stress states associated with thinning zones. The stressed states of the ferromagnetic walls of immersed pipelines form specific responses in an external magnetic field, while the actual thinning of the pipeline walls is detected by contact methods. The results of the surveys are reduced to a system parametrization of magnetometric non-destructive testing data within the framework of the developed automated workplace structure. The content of the conclusions is in the development of the principle for referenceless recognition of risky sections of the pipeline as a fully automated component of diagnostician’s workplace.

The paper proposes an alternative method of atmospheric correction using the OLCI satellite data for the Black Sea as an example. Currently, for remote sensing problems, the standard Gordon and Wang atmospheric correction algorithm is used in most cases (GW94). Unfortunately, its operation is often accompanied by the appearance of negative values of the spectral radiance coefficient of the sea (remote sensing reflectance) rs( ) in the shortwave region, which means a sufficient number of physically incorrect values and subsequent incorrect calculation of the concentration of chlorophyll-a and yellow matter. In this paper, a simple algorithm is proposed, built exclusively on analytical formulas, where two procedures of interpolation and extrapolation are conceptually implemented simultaneously, extrapolation - via two channels, interpolation based on the constancy of the color index ratio (CI = rs(412)/ rs(443) = 0.8). Using individual examples of OLCI scanner data, the performance GW94 of the new algorithm was tested for different states of the atmosphere and sea surface by comparing the results with in-kind measurements of the AERONET-OC platforms, with Level-2 data and with the operation of the regional method of additional correction. The new algorithm was tested under the following conditions: clear atmosphere (presence of background aerosol), presence of dust aerosol, cloud boundaries, presence of sun glare, coccolithophore bloom. When analyzing a number of Sentinel 3A/3B satellite images, it was found that the new simple algorithm was, on average, better than the standard one, which means that there is a prospect for its improvement. The advantage of this approach is its universality and the possibility of its implementation for other water areas, if there are patterns in the variability of the "blue" color index.

A systematic earthquake prediction is performed regularly at fixed intervals within a preselected seismically homogeneous zone. The result of each prediction iteration is a map highlighting the alarm zones, where the epicenters of target earthquakes are expected. The proposed methodology introduces the following innovations: 1 – A prediction is considered successful if all epicenters of the target earthquakes during the forecast interval fall within the alarm zone. 2 – The methodology optimizes both the probability of successfully detecting earthquake epicenters across a series of forecasts and the success rate of predictions in each individual iteration. 3 – The methodology enables the estimation of the probability of success for the next forecast interval. Examples of the method's application are demonstrated for predicting earthquakes in Kamchatka, California, and the island region of Japan.

In the Bay of Aniva (Sea of Okhotsk) there is one of the carbon polygons where greenhouse gas balance studies are conducted. Wind waves play an important role in energy, material and gas exchange in the ocean-atmosphere and ocean-land systems, ensuring the transfer of matter and gases between all biotic and abiotic components. This paper presents an analysis of the wave height, period and wavelength based on the database of wave modeling from 1979 to 2019. The maps of the main parameters and their statistical distributions are analyzed. Wind and wave roses are presented for several points in different parts of the bay. The average long-term of significant wave height is up to ∼ 0.5 m in the northern part of the bay and up to ∼ 1 m in the southern part. The maximum significant wave height reaches 8.5 m in the southern part of the bay and about 4–5 m in the north. The most dangerous areas for waves are the southwest, south and southeast.

This study aims to provide 2D tomography images of surface wave group velocity in Armenia and its neighboring regions within the Eurasian-Arabic plates, aiming to enhance the understanding of the shear velocity structure in the area. In this context, ∼ 516 earthquakes (M ≥ 3.5) recorded by 20 stations between 1999–2018 were analyzed, and the surface wave group velocity dispersion curves for each record (source-station path) were estimated. Subsequently, taking advantage of a 2D-linear inversion procedure, 2D tomography maps for periods of 5–80 s (Depth ≈ 180 km) were computed with a grid spacing of 0.2◦ × 0.5◦. The results of this research indicate that short-periods (5 ≤ T ≤ 25 s) are more influenced by shallow, ever-evolving deformations within various geological units, such as sedimentary basins. A minor low-velocity anomaly (Depth ≈ 27 km) is observed on the northwest slope of the Aragats volcano, which contrasts with the findings of earlier studies. For Rayleigh and Love waves, the North Armenia Block is covered by a high-velocity anomaly. The results for medium periods reveal the presence of very-high-velocity anomalies in some geological units (e.g., Lesser Caucasus), aligning with the ongoing subduction processes. In contrast, very lowvelocity anomalies reflect the uppermost mantle information, revealing an extremely thin lithosphere accompanied with a hot asthenosphere. The findings for long-periods of Love and Rayleigh waves in Armenia reveal an almost uniform velocity distribution pattern, along with very-low-velocity anomalies in the uppermost mantle, attributed to a thin lithosphere or the lack of lithospheric mantle in most units of the study region. The results demonstrate an acceptable accordance with known geological features in the Eurasian-Arabic ongoing collision zone. Overall, the main strengths of this paper lie in the application of a tomographic technique utilizing an important data set. The findings have the potential to provide new insights into the Armenian region and its surrounding areas.