Los Alamos AI Takes Big Step In Predicting Earthquakes
A breakthrough in earthquake prediction has been made by scientists at Los Alamos National Laboratory using advanced artificial intelligence. By analyzing seismic data from the Kīlauea volcano in Hawaii, researchers were able to detect hidden signals that precede earthquakes, particularly in stick-slip faults that can cause significant destruction.
The team, led by seismologist Christopher Johnson, used machine learning to identify these warning signals within seismic data collected by the U.S. Geological Survey’s Hawaiian Volcano Observatory. By focusing on specific time windows and analyzing unique patterns in the data, researchers were able to predict when a fault is nearing a major slip that results in an earthquake.
This groundbreaking research has implications beyond the Kīlauea volcano, suggesting that similar methods could be used to assess earthquake hazards worldwide. By studying the continuous acoustic emissions generated by tectonic plates rubbing against each other, scientists were able to infer important physical properties of faults such as displacement, friction, and thickness.
The study, published in Geophysical Research Letters, marks the first successful application of this approach to seismogenic faults, shedding light on the predictive capabilities for stick-slip events like those observed at Kīlauea. By analyzing ground displacement data and seismic signals, researchers were able to estimate ground movement and time to the next fault failure with remarkable accuracy.
This research builds on previous work conducted by Los Alamos on faults in California and the Pacific Northwest, where machine learning was proven effective in detecting precursory signals. By understanding the unique patterns in seismic noise, scientists can track the evolution of faults and determine their current state in the slip cycle, providing valuable insights into earthquake prediction.
In conclusion, the latest breakthrough by Los Alamos scientists represents a significant step forward in earthquake prediction, with the potential to enhance global efforts to mitigate seismic risks. By harnessing the power of artificial intelligence and machine learning, researchers are paving the way for more accurate and timely earthquake forecasts, ultimately helping to save lives and safeguard communities against natural disasters.
