Using the Self-Organized Criticality Approach for Modeling Pre-Seismic Electromagnetic Emissions

We present a new approach to modeling electromagnetic emission signals generated in the Earth's crust prior to major earthquakes. The approach is based on a non-Abelian stochastic directed sandpile cellular automaton representing cooperative dynamics of rock cracks before and during the earthquake onset. When driven slowly, the automaton tends naturally to the state of self-organized criticality in which scale-free dynamics is observed in the form of power-law probability distributions of instability parameters as well as fractal geometry of seismic stress accumulation. Based on this model, we investigate numerically the possibility of using a fractal time-series analysis of pre-seismic electromagnetic emissions as a method for prediction of catastrophic seismic events