Teimuraz Matcharashvili

Detecting differences in temporal distribution of small earthquakes before and after large events

We have evaluated the dynamical properties of the temporal distribution of the small earthquakes. Two main goals of the investigation were: (a) a qualitative evaluation of the nonlinear structure of the time distribution of earthquakes, taking place before and after the strongest Caucasian events; (b) a quantitative discrimination of the dynamics (of time distribution of earthquakes) preceding and following the largest regional earthquakes.The dynamical characteristics of seismicity before and after four recent large earthquakes in the Caucasian region have been investigated. Nonlinear time-series analysis techniques, such as calculation of the correlation dimension for sliding windows and surrogate data analysis tests have been used; inter-event time-interval sequences have been considered as a time series.It was determined that the dynamics of lithospheric processes, generating the temporal distributions of earthquakes, do not change qualitatively before and after the largest Caucasian earthquakes. Inter-event time-interval sequences reveal low-dimensional nonlinear structure in both situations.On the other hand, quantitative analysis shows that the low-dimensional nonlinear structure of the temporal distributions of earthquakes after the largest events is significantly different than those before the largest events.

Discrimination between stochastic dynamics patterns of ambient noises (Case study for Oni seismic station)

Investigation of complex dynamics of ambient seismic noise remains as an important scientific research challenge. In this work we investigated dynamical features of the ambient noises at Oni seismic station, Georgia. We used stochastic model reconstruction method from measured data sets. Seismic records for different time periods around Oni seismic station have been analysed.It was shown that the dynamics of fluctuations of seismic noise vertical component undergoes essential changes for considered time period from 2005 to 2012. These changes are more noticeable for time periods of preparation and aftershock activity of strong M6.0 earthquake occurred in 2009 in the vicinity of Oni seismic station.

Dynamical Patterns in Seismology

Earthquakes are important components of complex dynamical Earth systems known as geocomplexity. One of the main contributors to geocomplexity is the seismic process which notoriously displays nonlinear behaviors including the self-organization of many interacting components (tectonic plates, faults). These processes result in seismic (macro-scale) events of collective behaviors in the temporal, spatial and energy domains. In the chapter the results of both active and passive experiments on triggering/synchronization are presented. The dynamic patterns of seismicity are revealed by the application of nonlinear dynamics tools to time series from: “laboratory” earthquakes (acoustic emission during natural stick-slip and stick-slip under weak periodic forcing), regional seismicity of the Caucasus Mountains, local seismicity in the area of large reservoir during its construction and regular exploitation, as well as from analysis of variations in local seismicity in a Central Asia test area due to application of strong electric pulses. The review of recent results on dynamic triggering of local seismicity by remote earthquakes is also presented. It is shown that relatively weak external forcings can induce clear changes in modeled and real earthquake dynamics. Recurrence Quantification Analysis (RQA) proved to be an efficient method for finding hidden nonlinear structures is seismic time series. Quoting Webber and Zbilut (2005): “…whatever the case, whether it be forecasting dynamical events in the medical field, geophysics, or meteorology, the future of recurrence analysis looks bright and promising.”

Investigating the dynamical features of the time distribution of the reservoir-induced seismicity in Enguri area (Georgia)

We analyzed the fractal and multifractal properties of the earthquake time series occurred around the Enguri dam in West Georgia by applying the methods of detrended fluctuation analysis and multifractal detrended fluctuation analysis. We examined the interevent time series in two periods: (1) 1960–1980, in which the investigated area was characterized by the natural seismicity; and (2) 1981–2012, in which the quasi-periodic change of the reservoir water level affected the earthquake generation. Our findings show that the water level variation may influence the fractal properties of earthquake temporal distribution in the local area around the Enguri dam. In particular, it is observed that the time distribution features of seismicity occurred in the second period are more persistent than the natural seismicity occurred in the first period. Furthermore, the seismic process of the second period shows a lower multifractal degree than that of the first period, indicating that the influence of quasi-periodic fluctuation of water level features the seismicity as more regular compared to the natural seismicity.

Scaling features of ambient noise at different levels of local seismic activity: A case study for the Oni seismic station

Investigation of dynamical features of ambient seismic noise is one of the important scientific and practical research challenges. We investigated scaling features of the ambient noises at the Oni seismic station, Georgia, using detrended fluctuation analysis method. Data from this seismic station, located in the epicentral zone of Oni M6.0, 2009, earthquake, were selected to include time periods with different levels of local seismic activity.It was shown that the investigated ambient noise is persistent long-range correlated at calm seismic conditions in the absence of earthquakes. Fluctuation features of the analyzed ambient noises were affected by local earthquakes, while remote seismic activity caused just slight quantitative changes. Processes related to the preparation of a strong local earthquake may cause quantifiable changes in fluctuation features of ambient noises. Fluctuation features of seismic noise for periods of increased local seismic activity cease to be long-range correlated and appear to become a complicated mixture of random and correlated behaviours.

Analysis of the Complexity of Seismic Data Sets: Case Study for Caucasus

Abstract The investigation of the dynamics of complex seismic processes remains a major scientific challenge. Presently this problem is viewed in the light of modern concepts of the spatiotemporal behaviour of highly nonlinear or complex natural systems. The significant progress in this direction achieved over recent decades has paved a new avenue of research in the investigation of qualitative and quantitative aspects of the dynamics of seismic processes. Special attention has been paid to the elaboration of new methods of measuring the complexity of both global and local dynamics from seismic data sets. In this chapter, we present examples using several modern data analysis approaches on data sets related to seismic activity in the Caucasus. These data analysis methods are often used for the qualitative and quantitative evaluation of the complexity of natural processes, including seismic processes in different parts of globe.

The Analysis of Variability of Short Data Sets Based on Mahalanobis Distance Calculation and Surrogate Time Series Testing

In this work, we present convenient for short time series approach which is based on the multivariate Mahalanobis distance calculation, combined with the surrogate time series testing. In order to test the ability of this approach to differentiate changes which could occur in complex processes, we analyzed data sets of different origins. We used seismological, meteorological, physiological, and economic data sets. Exactly, we analyzed data sets of inter earthquake times (IET), inter earthquake distances (IED), and differences in consecutive magnitudes (DM) compiled from southern Californian earthquake catalogue, data sets of yearly number of warmer and colder days derived from maximal air temperature data bases in Tbilisi, Georgia, arterial systolic, and diastolic blood pressure time series of healthy persons, as well as components of Index of Economic Freedom (IEF) and exchange rate time series of three southern Caucasian countries. It was shown that used approach, even in the case of relatively short time series, may effectively be used to quantify dynamical changes occurred in different natural complex processes.