Random stress and Omori's law

TL;DR

This paper introduces new statistical distributions combining power-law stress models with Levy and Inverse Gaussian distributions to better explain Omori's law of aftershock decay, supported by analysis of earthquake data.

Contribution

The paper derives novel mixed distributions that incorporate power-law stress effects into Levy and IGD models, improving the explanation of aftershock decay patterns.

Findings

New distributions closely resemble Omori's law.

Analysis of earthquake catalogs supports the theoretical models.

Parameters can be estimated through statistical analysis or laboratory experiments.

Abstract

We consider two statistical regularities that were used to explain Omori's law of the aftershock rate decay: the Levy and Inverse Gaussian (IGD) distributions. These distributions are thought to describe stress behavior influenced by various random factors: post-earthquake stress time history is described by a Brownian motion. Both distributions decay to zero for time intervals close to zero. But this feature contradicts the high immediate aftershock level according to Omori's law. We propose that these statistical distributions are influenced by the power-law stress distribution near the earthquake focal zone and we derive new distributions as a mixture of power-law stress with the exponent psi and Levy as well as IGD distributions. Such new distributions describe the resulting inter-earthquake time intervals and closely resemble Omori's law. The new Levy distribution has a pure power-law form with the exponent -(1+psi/2) and the mixed IGD has two exponents: the same as Levy for small time intervals and -(1+psi) for longer times. For even longer time intervals this power-law behavior should be replaced by a uniform seismicity rate corresponding to the long-term tectonic deformation. We compute these background rates using our former analysis of earthquake size distribution and its connection to plate tectonics. We analyze several earthquake catalogs to confirm and illustrate our theoretical results. Finally, we discuss how the parameters of random stress dynamics can be determined through a more detailed statistical analysis of earthquake occurrence or by new laboratory experiments.