Beneath the spectacular landscapes of Yellowstone National Park lies seismic activity far more intense than previously thought. A recent study has uncovered thousands of previously undetected earthquakes using artificial intelligence.
The application of AI to analyze seismic data revealed nearly 86,000 earthquakes over a 15-year period—a figure significantly higher than previous estimates. This discovery provides a more accurate picture of the geological activity beneath Yellowstone, highlighting seismic swarms along immature faults.
The Grand Prismatic, Yellowstone's hot spring, is fed by a magma chamber. Its vibrant colors come from hydrophilic bacteria.
Image Wikimedia
Unlike aftershocks, seismic swarms are clusters of small, interconnected earthquakes that occur over a short period. These phenomena, now better documented, could help improve safety measures and the development of geothermal energy.
Researchers used fractal models to characterize fault roughness—an innovative approach that could be applied to other volcanic regions.
What is a seismic swarm?
A seismic swarm is a series of small earthquakes occurring in a confined area over a short period. Unlike aftershocks, they do not follow a mainshock and may indicate unique geological activity, such as fluid movement beneath the surface.
These swarms are often associated with volcanic regions, where magma and groundwater interact with rock. Studying them provides deeper insights into geological processes and helps anticipate potential eruptions.
The seismic swarms beneath Yellowstone were detected along immature faults, whose roughness promotes this type of activity. This discovery could aid in identifying at-risk zones in other volcanic areas.
AI benefits seismology
Artificial intelligence enables rapid analysis of vast seismic datasets, revealing earthquakes too small or closely spaced to be detected manually. This technology marks a new era in earthquake research.
By applying machine learning algorithms to historical data, researchers can identify patterns and correlations invisible to the human eye. This approach has increased the number of known Yellowstone earthquakes tenfold.
Its use is expected to become widespread in the coming years, transforming our understanding of global seismic activity.