An AI algorithm predicts slow earthquakes

The Indonesian island of Lombok was hit by an earthquake in 2018. Photo: AFP / Fred Dufour via AFP Relaxnews

A team of researchers has succeeded in creating an artificial intelligence (AI) algorithm that can identify the changes in the Earth’s crust that occur three months before an earthquake.

On August 21, a 6.9 magnitude earthquake jolted Indonesia. Fortunately, it was a highly concentrated earthquake that did not result in loss of life or material damage. However, the country, which sits on the Pacific Ring, has a proven record of extremely dangerous seismic activity. Most recently in 2018, the archipelago was struck by a magnitude 7.5 earthquake, which was part of a series of earthquakes and tsunamis that have claimed thousands of lives in the country.

Scientists are now wondering whether devastation of this scale could be avoided using systems developed by artificial intelligence, among them a team of researchers from the French High School of Normale-Superior (ENS), which recently announced the discovery of an AI algorithm for predicting seismic events in the journal Nature Communications.

Focus on “slow” earthquakes

This latest research project adopted a simple approach that involves feeding a deep learning machine with large amounts of seismic data recorded before an earthquake strikes. The goal was to develop an algorithm with the ability to detect the recurring phenomena that lead to a major seismic event.

The machine was initially trained using laboratory earthquakes, before it was adapted to look for signs of “slow” earthquakes under Vancouver Island, Canada. Seismic events of this type, which share many characteristics with rapid and most destructive earthquakes, can last for weeks or even months. Since it is slow, it hardly generates any seismic waves and as a result does not cause much damage. At the same time, the fact that it has occurred over a long period makes it easier to analyze.

Promising results

The algorithm generated a list of the characteristics that precede the emergence of earthquakes. Among them, the researchers observed a massive increase in seismic energy before the rupture, as if more and more small seismic waves were emitted from the seismic zone. These crackles were noticeable for up to three months before a slow earthquake was usually detected, which means that the occurrence of these phenomena can be predicted in advance.

The AI ​​agent also discovered that tremors start on a very small scale and then accelerate before becoming visible to the naked eye, as occurs in rapid earthquakes.

What about detection of major earthquakes?

As it stands, there has been little progress towards this goal.

“If you look at this question in terms of time scales: a slow earthquake lasts for a month, and past signals can be detected for 100 days (just over three months) before the event. Claudia Holbert and Roman Gullivitt in a regular explanation of their work published in The Conversation,” said: A major earthquake of great strength lasts for 10 to 100 seconds, which means that previous signals should be noticed 30 to 300 seconds before they happen …

However, as it is, none of this has been proven, and perhaps more than that, what are we going to do with the warning that comes only five minutes before the disaster? Damaging earthquakes are also relatively rare, which means researchers do not have enough seismic data to train AI to predict them. Further study of seismic event mechanisms so that they can be modeled by computers and ultimately predicted appears to be the most promising research strategy at the moment. JB

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