AI News, Applying machine learning tools to earthquake data offers new insights
- On Tuesday, June 5, 2018
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Applying machine learning tools to earthquake data offers new insights
In a new study in Science Advances, researchers at Columbia University show that machine learning algorithms could pick out different types of earthquakes from three years of earthquake recordings at The Geysers in California, one of the world's oldest and largest geothermal reservoirs.
The repeating patterns of earthquakes appear to match the seasonal rise and fall of water-injection flows into the hot rocks below, suggesting a link to the mechanical processes that cause rocks to slip or crack, triggering an earthquake.
But looking at an earthquake's frequency information instead allowed the researchers to apply machine-learning tools that can pick out patterns in music and human speech with minimal human input.
The machine-learning assist helped researchers make the link to the fluctuating amounts of water injected belowground during the energy-extraction process, giving the researchers a possible explanation for why the computer clustered the signals as it did.
If the earthquakes in different clusters can be linked to the three mechanisms that typically generate earthquakes in a geothermal reservoir -- shear fracture, thermal fracture and hydraulic cracking -- it could be possible, the researchers say, to boost power output in geothermal reservoirs.
If engineers can understand what's happening in the reservoir in near real-time, they can experiment with controlling water flows to create more small cracks, and thus, heated water to generate steam and eventually electricity.
In a series of experiments, he and study coauthor Arthur Paté, then a postdoctoral researcher at Lamont-Doherty, confirmed that humans could distinguish between temblors propagating through the seafloor or more rigid continental crust, and originating from a thrust or strike-slip fault.
When the researchers matched the clusters against average monthly water-injection volumes across The Geysers, a pattern jumped out: A high injection rate in winter, as cities send more run-off water to the area, was associated with more earthquakes and one type of signal.
- On Monday, February 24, 2020
2017 Natural Sciences & Engineering Co-Research of the Year Holzman
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