LANL seismologist doing breakthrough earthquake research

LOS ALAMOS, N.M. (KRQE) – Research being done in New Mexico is showing promise when it comes to addressing a worldwide concern.

Researchers may be getting closer to one day being able to predict the next earthquake. Los Alamos National Labs seismologist Paul Johnson says this is breakthrough research.

“We’re learning new things about the system that we didn’t know existed,” he said.  Johnson and a researcher from Pen-State are using a so-called earthquake machine to make quakes in a lab.

Johnson is collecting sound information from that machine using a stethoscope of sorts. What is new here is the use of machine learning or artificial intelligence.

He says they are finding a vast amount of new information using the computer science approach about how a fault slip starts, ends and what happens between fault slips.

This research could help scientists predict earthquakes, although they are not quite there yet and do not know when they will be.

“It shows the power of applying these machine learning approaches even though it’s laboratory earthquake data, it’s earthquake data and it’s working extremely well, better than any of us could ever have imagined,” Johnson said.

Most recently, we saw the devastation a magnitude 8.1 earthquake left in Mexico City and southwestern Mexico. Johnson says scientists know a powerful tremor is overdue in our Pacific Northwest and any advancements in earthquake detection can be extremely helpful.

The next step, Johnson says is applying this in lab research to the actual earth.

This summer, Johnson was able to get his research published in an earth science journal. In the coming weeks, he hopes to publish more of his work. provides commenting to allow for constructive discussion on the stories we cover. In order to comment here, you acknowledge you have read and agreed to our Terms of Service. Users who violate these terms, including use of vulgar language or racial slurs, will be banned. Please be respectful of the opinions of others. If you see an inappropriate comment, please flag it for our moderators to review.

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