UNCORRECTED PROOF 1 2 Complexity of seismic process; measuring 3 and applications — A review 4 T. Chelidze ⁎ , T. Matcharashvili 5 M.Nodia Institute of Geophysics, 1, Alexidze str., 0193, Tbilisi, Georgia 6 Received 28 December 2005; accepted 18 May 2006 7 Abstract 8 Recent methods of analysis of so called disordered systems show that many objects and processes that earlier were considered 9 as completely random reveal clear evidence of having some ordered structure in both time and space. These new methods (fractals, 10 percolation, nonlinear dynamics and complexity theories) allow visualization and quantitative assessment of the level of 11 complexity (orderliness) of these structures, using both theoretical models and experimental data. We consider sequentially some 12 aspects of structural and evolutionary complexity of dynamics of seismic process and the technique of measuring this property. 13 It is shown that the physical properties of geophysical medium are not always self-consistent and manifest fractal behavior on 14 selected spatial and temporal scales. Mechanical percolation theory can be used for modeling geometry of fracture process. 15 Namely, we consider fractal and connectivity aspects of delayed failure, including energy emission during fracturing. Special 16 attention is paid to relating the intensity of geophysical anomalies to the strain in the framework of the pressure-induced anomalous 17 strain-sensitivity (percolation) model, which explains naturally the observed heterogeneity of response of a geophysical media to 18 the strain variation. 19 Different methods of measuring the dynamic complexity of seismological time series are applied to magnitude and waiting time 20 sequences of Caucasian earthquakes. The fractal (correlation) dimension d 2 of the latter is high (larger than 8), but the former one 21 has as low dimension as 1.6–2.5, which makes waiting time sequences a promising tool for revealing precursory changes. 22 The same nonlinear technique allow detecting significant changes in the seismic regime during external electromagnetic forcing 23 by MHD pulses; similar tests on the laboratory scale show the possibility of triggering/controlling stick-slip process by relatively 24 weak electromagnetic or mechanical forcing. 25 Lastly, the predictive potential of complexity analysis of seismological time series is considered. For example, percolation 26 model predicts the increase of the number of large events and the scatter of magnitudes of events, decrease of the magnitude- 27 frequency relation slope and appearance of multifractality at approaching the final rupture. 28 It seems that seismology can benefit from using the new techniques to cope with the complexity of earthquake machine; for 29 example, the measures of complexity can be characteristic for a given region and change before strong earthquake. 30 © 2006 Published by Elsevier B.V. 31 32 Keywords: Seismic process; Percolation; Strain-sensitivity; Measuring complexity; Time series 33 Tectonophysics xx (2006) xxx – xxx + MODEL TECTO-07855; No of Pages 11 www.elsevier.com/locate/tecto ⁎ Corresponding author. E-mail address: chelidze@ig.acnet.ge (T. Chelidze). 0040-1951/$ - see front matter © 2006 Published by Elsevier B.V. doi:10.1016/j.tecto.2006.05.029 ARTICLE IN PRESS Please cite this article as: T. Chelidze, T. Matcharashvili, Complexity of seismic process; measuring and applications — A review, Tectonophysics (2006), doi:10.1016/j.tecto.2006.05.029