z-logo
open-access-imgOpen Access
Statistical analysis of synthetic earthquake catalogs generated by models with various levels of fault zone disorder
Author(s) -
Lu Chunsheng,
VereJones David
Publication year - 2001
Publication title -
journal of geophysical research: solid earth
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.67
H-Index - 298
eISSN - 2156-2202
pISSN - 0148-0227
DOI - 10.1029/2000jb900452
Subject(s) - akaike information criterion , predictability , fractal , magnitude (astronomy) , statistical physics , sensitivity (control systems) , scale (ratio) , asperity (geotechnical engineering) , fault (geology) , geology , mathematics , physics , seismology , statistics , mathematical analysis , astrophysics , geotechnical engineering , quantum mechanics , electronic engineering , engineering
The stress release model, a stochastic version of the elastic rebound theory, is applied to the large events from four synthetic earthquake catalogs generated by models with various levels of disorder in distribution of fault zone strength ( Ben‐Zion , 1996). They include models with uniform properties (U), a Parkfield‐type asperity (A), fractal brittle properties (F), and multi‐size‐scale heterogeneities (M). The results show that the degree of regularity or predictability in the assumed fault properties, based on both the Akaike information criterion and simulations, follows the order U, F, A, and M, which is in good agreement with that obtained by pattern recognition techniques applied to the full set of synthetic data. Data simulated from the best fitting stress release models reproduce, both visually and in distributional terms, the main features of the original catalogs. The differences in character and the quality of prediction between the four cases are shown to be dependent on two main aspects: the parameter controlling the sensitivity to departures from the mean stress level and the frequency‐magnitude distribution, which differs substantially between the four cases. In particular, it is shown that the predictability of the data is strongly affected by the form of frequency‐magnitude distribution, being greatly reduced if a pure Gutenburg‐Richter form is assumed to hold out to high magnitudes.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here