Mathematical model identifies acoustic signal preceding seismic shake

Researchers have identified a unique acoustic signature that may precede seismic ruptures.

In the lab, scientists deployed an earthquake machine to produce seismic waves. Researchers used numerical simulations to analyze the seismic signatures produced by the synthetic ruptures.

Their analysis -- detailed this week in the journal Physical Review Letters -- revealed a unique acoustic signal preceding the seismic rupture.

"Previous machine-learning studies found that the acoustic signals detected from an earthquake fault can be used to predict when the next earthquake will occur," Ke Gao, a computational geophysicist at Los Alamos National Laboratory, said in a news release. "This new modeling work shows us that the collapse of stress chains inside the earthquake gouge emits that signal in the lab, pointing to mechanisms that may also be important in Earth."

Stress chains are formed by a bridge of molecules linking each side of the fault block. Stress can be transported from one side of the block to the other via the molecular bridge.

According to the new research, analysis of the acoustic signal can offer scientists a status update on the stress present in the fault. Previous studies have identified the same kind of acoustic signals within real fault systems.

By analyzing the signals in the lab, scientists are beginning to understand what exactly they mean and how they can be used to predict an impending rupture.

"Using the numerical model that we developed at Los Alamos, we examine and connect the dynamics in a granular system of fault gouge to signals detected on passive remote monitors," Gao said.

To identify the stress-releated mechanisms behind the signals, scientists relied on numerical models run by supercomputers at Los Alamos. The models were able to simulate grain-to-grain interactions and analyze how stress influences the acoustic signals produced by the granular system.

The models successfully simulated the ways a fault's evolution alters grain-to-grain interactions. The simulations also reproduced the formation and evolution of stress chains.

Thanks to the simulations, scientists are beginning to understand how acoustic signals can reveal the evolution of stress within a fault structure. Eventually, these acoustic signals could be used to predict earthquakes many hours, perhaps days, in advance.

"The stress chains endow the layer with resistance to shear and on failure launch broadcasts into the formation," researchers wrote in their paper. "These broadcasts, received as acoustic emission, provide a remote monitor of the state of the granular layer of the earthquake system."

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