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Application of pattern recognition techniques to earthquake catalogs generated by models of segmented fault systems in three-dimensional elastic solids

Mariana Eneva, & Yehuda Ben-Zion

Published November 10, 1997, SCEC Contribution #372

Techniques and seismicity parameters described by Eneva and Ben-Zion [1997] are used to examine synthetic earthquake catalogs generated by Ben-Zion [1996] for precursory patterns of large model events. Different model realizations represent various levels of fault zone disorder. These include models with uniform properties (U), a Parkfield-type asperity (A), fractal brittle properties (F), and multi-size-scale heterogeneities (M). The seismicity parameters used are based on information contained in typical earthquake catalogs reflecting earthquake distribution in space, time, and size. The analysis highlights the complexity of the information content of the synthetic earthquake catalogs. Simple repetitive precursory signals have not been found. However, local extrema in the examined parameters are found to have significant association in time with large events. Thus our techniques and parameters may be useful for intermediate-term earthquake prediction, especially when parameters are used in combinations. Some analysis results are the same for all model realizations and some depend on the model. Features characterizing all catalogs are as follows: (1) Large model events are statistically predictable on the basis of patterns in the distribution of smaller events. (2) For a given parameter, the type of precursory extrema (maxima or minima) is the same for all models. (3) The interparameter correlation for any parameter pair has the same sign (positive or negative) in all models. (4) The large events are neither slip-nor time-predictable based on previous large events. Results that differ from model to model include the following: (1) The degree of predictability of large events correlates with the degree of regularity in the assumed fault properties, following the order U, F, A, and M. (2) There is no one-to-one correlation between type of precursory extrema (maxima or minima) and type of precursory trends (increase or decrease); this produces great variations in observable trends for any given parameter, both from model to model and for different events in the same model. (3) The interparameter correlations vary among models, with the highest correlations in model F. Most discussed patterns are in agreement with observations from seismically active zones, laboratory models, and mining-induced seismicity.

Eneva, M., & Ben-Zion, Y. (1997). Application of pattern recognition techniques to earthquake catalogs generated by models of segmented fault systems in three-dimensional elastic solids. Journal of Geophysical Research, 102(B11), 24513-24528. doi: 10.1029/97JB01857.