Seismic Instruments最新文献

Features of rock deformation and destruction can be traced at different scale levels. Detecting peculiarities of rock destruction under intense deformation is essential for understanding the patterns of rock mass evolution. Here we propose a method of segmentation of images of petrographic thin sections and detection of intact areas and grains to identify microstructural properties of rocks. The segmentation method is based on the combination of a special technique of microstructural analysis (STMA) developed at IGEM RAS and the Richer convolutional features (RCF) multilayer neural network. Estimating the error of determining the size of segments due to a false detection of lineaments (STMA algorithm) and inaccuracy of edge detection (RCF algorithm) was performed basing on the Monte Carlo simulation. The method was used to segment 234 thin sections of rocks making up the central part of Primorsky fault of the Baikal Rift Zone and representing different types of tectonites. Analysis of segmented images showed that at scales from 10^–5 to 10^–2 m, in 44% of cases, the rock structure obeys a lognormal distribution of the areas of intact segments, and in 3% of cases, a power distribution. The Weibull distribution does not describe the statistics of the areas of intact segments. The result indicates that fragmentation of rocks is not a scale invariant process.

Contemporary technologies have simplified and made accessible the collection and processing of data from scientific observations. Current solutions enable rapid preliminary processing of collected data, cleansing it of outliers related to measurement errors and filling gaps in fragmented time series. However, the ease with which this is achieved presents risks of indiscriminate use of such solutions. Consequently, data indicating real physical anomalies may be discarded, and the amalgamation of time series fragments might result in data that does not correspond to the observed processes and phenomena. Such a situation was justified in the past when there was a scarcity of computational resources. Discarding inherently unreliable values and filling gaps simplified and accelerated data analysis. Now, with sufficient computational power available, it is possible to begin searching for patterns in what was previously considered observational error and discarded. Moreover, the volume of accumulated data may allow for the consideration of fragments of time series as parts of a regular process, without filling the gaps with artificial data created based on our assumptions about the nature of the observed processes and phenomena. This raises the question of the necessity to adapt the approaches used in collecting and analyzing observational results to the possibilities afforded by new computational tools.

Today, an urgent trend in geology is the development of approaches to applying neural network technologies at different stages of geological exploration. The article considers the architecture of the AlexNet neural network, which has already been tested in various territories. AlexNet makes it poddible to conduct training on a relatively small amount of data with sufficient accuracy to solve problems. To carry out operations with the selected neural network, a technique has been developed that makes it possible, based on prepared geological and spatial features (criteria) that indirectly or actually control ore objects, to train a neural network model with its further application to the studied territory. This approach allows one to analyze and obtain an expert assessment of the studied area in the form of a spatial predictive search model that predicts the location of the most promising sites for further study. In the current article, an example of using the developed methodology for forecasting hydrothermal massive sulfide deposits in the territory of Southeastern Transbaikalia is demonstrated.

In the lack of empirical data in the study area, the level of parameters of seismic oscillations—accelerations, velocities, displacements, etc.—is specified either using the instrumental part of seismic intensity scales or by recalculating intensity estimates into e oscillation parameter values of interest using correlation relationships. Both the seismic intensity values and the values of seismic ground motion parameters are continuous quantities. Because in practice intensity ratings are rounded to integer values, the intensity and parameters of seismic oscillations are considered discrete quantities. As a result, the quantitative characteristics of seismic oscillations at the boundary of neighboring points have a jump in the calculated seismic ground motion parameters. Consequently, each integer point in reality corresponds not to a single value of the oscillation parameter, but to a certain interval of values. In this article, based on an analysis of empirical data, ranges of values of seismic oscillation parameters are established: peak ground accelerations, velocities, and displacements corresponding to both integer and fractional (rounded to half a point) seismic intensity values, with respect to the seismic intensity scale GOST R 57546-2017. The problem of determining the ranges of predominant periods and duration of seismic oscillations is also considered. The problem of increasing the accuracy of seismic treatment assessment is discussed.

Some aspects of the seismicity of Turkmenistan and adjacent territory of Northern Iran are considered based on the ISC catalog for the period from 1964 to 2021. This period is apparently the most complete and, therefore, allows one to fairly correctly draw conclusions regarding some aspects of the seismicity of Turkmenistan and Northeastern Iran. In total, the catalog for the specified period contains about 500 events with a magnitude greater than 2.5. It is shown that the occurence graph has a negative slope slightly above average, which indicates a low value of the fractal characteristics of the environment in the Turkmenistan–Northern Iran region. Over the past 57 years, seismic activity in the region has varied from year to year. Moreover, from 1964 to 1984, seismic activity increased noticeably, and from 1985, it stabilized until 2000. From 2001 to 2004, there has been a sharp decline in seismic activity in Turkmenistan and Northern Iran, and from 2005 to 2016, a gradual increase in seismic activity in the region, followed again by a decrease. Lastly, since 2019, there has again been a significant increase in activity.

The effect on seismic impacts of a thin low-velocity layer overlying a high-velocity rock, which is typical of crystalline shields of ancient platforms, is studied. The initial data for the analysis are the response spectrum and accelerograms compatible with them on bedrock. The peak acceleration value (PGA) is assumed to be 0.11 g, which approximately corresponds to a shaking intensity of 7 (MSK64 scale). The site response was calculated using the Monte Carlo approach using equivalent linear modeling for four models differing in the thickness of the upper layer. It is shown that even a slight increase in the thickness of the low-velocity layer can lead to noticeable increase of the peak acceleration of ground motion and a change in the shape of the response spectrum. The result warns against accepting the seemingly intuitively correct assumption that a slight change in soil thickness (adding 1 m of soil) will have virtually no effect on the parameters of seismic motion on the surface.

The earthquake on May 15/28, 1903, is not a newly discovered unknown seismic event. Analysis of its information background highlighted that original macroseismic evidences from regional Russian press contemporary to the earthquake were not used. Meanwhile interpretation of early-instrumental seismic records does not provide accurate location of the epicenter, though the magnitude can be estimated rather precisely. In this study, original evidence on macroseismic effects of May 15/28, 1903, is assembled, based on which the location of the epicenter is estimated and the accuracy thereof is evaluated. The magnitude is assumed from earlier published studies and is not re-evaluated in this paper. Finally, according to our study, the epicenter is shifted in NW direction by 15 km that relative to previous solutions; accuracy of location ca. 8 km. This, in general, small change in epicenter location shows the activity of SE–NW oriented structures.

At the Verkhnekamskoe salt deposit, a monitoring system for the emergency area has been implemented, including a distributed acoustic sensing with a 6-km optical line and an active borehole source of elastic vibrations. Monitoring is performed using cross-well seismic survey. The use of a special cable containing straight and spiral fiber makes it possible to record both direct and refracted waves. Based on a comparison of wave fields, areas of change in the elastic properties of the massif are located and a quantitative assessment of such changes is given. The use of a large number of simultaneously recording channels makes it possible to achieve the required spatial resolution depending on the task. The low cost of fiber optic cable makes it possible to design its permanent installation in emergency areas with limited access. The proposed monitoring system can be used both to monitor the safety of the developed massif in problem areas, and to monitor the foundations of critical buildings and structures located in zones of accelerated subsidence of the undermined territory.

Over past decades, the scope and number of national Global Navigation Satellite Systems (GNSS) have rapidly increased. To determine a geodetic position with high accuracy, many different GNSS receivers are used. The data from them are presented in common RINEX format for information exchange and further processing. By the 45th anniversary of the scientific activities of the Research Station of the Russian Academy of Sciences in Central Asia, we have collected an archive of GNSS observations, which includes about 300 000 days of fixing positions for more than 1500 geodetic reference sites with a data recording frequency of 30 s. The quality of coordinate calculations and site displacement velocity strongly depends on correct formatting of source data in RINEX files. This is clear from the experience of working with the high-precision software packages GAMIT/GLOBK and Bernese GNSS Software. We have created the RinexVER program for stream fixing of typical errors during processing of a large number of daily RINEX files (10 000–15 000 observations per year), for their sorting and formation of a structured archive, and for collecting the necessary information about them. Thus, the work of an expert on fixing RINEX file can be reduced by 50 times. In addition, it is possible to increase the accuracy in calculating time series of coordinates and velocity vectors for observation sites in geodynamic studies.

It has been suggested that extremely low frequency (ELF) emissions can serve as an indirect remote means of detecting overloads in the operation of energy networks caused by geomagnetically induced currents (GICs). An analysis of the data from the recording system for GIC in power line transformers, a magnetometer, and an ELF receiver on the Kola Peninsula during a magnetic storm on September 7–8, 2017, showed that the intensity of radiation at an industrial frequency of 50 Hz and its third harmonic of 150 Hz increases with increasing GIC. Apparently, under the influence of GIC, the transmitted currents in power transmission lines (PTLs) are unbalanced, so that the PTL becomes a large-scale antenna and radiates both at the fundamental frequency of alternating current (50 Hz) and its harmonics. The discovered effect of the increasing imbalance of currents in PTLs has not previously been noted as a possible factor in the impact of space weather on energy systems.