2023 Author: Bryan Walter | [email protected]. Last modified: 2023-05-21 22:24
Scientists have shown that the vibrations of the soil created by the passage of heavy trains can be used to sound the crust to a depth of several kilometers. This makes it possible to detect abrupt changes in the speed of propagation of seismic waves near faults, which is associated with an imminent earthquake, the authors write in the journal Geophysical Research Letters.
Reliable earthquake prediction remains one of the main unsolved problems of seismology. Several possible approaches to its solution have been proposed, but they are either difficult to implement or do not give a sufficiently high-quality forecast.
One of the described methods relies on a jump in the seismic wave velocity near a crustal fault, since laboratory experiments predict this behavior in the case of a fast earthquake. Theoretically, this makes it possible to find dangerous areas ahead of time, but in reality this requires constant operation of powerful sources of seismic disturbances, which is practically impossible to implement due to the extremely high cost.
Scientists from France, Belgium and the United States, led by Florent Brenguier of the University of Grenoble-Alpes, describe the possibility of using vibrations generated by trains to probe the Earth's crust. Researchers have long known that heavy freight trains generate seismic noise, but until recently it was believed that it could only penetrate short distances inland. In 2018, however, an article appeared describing the successful recording of train-induced ground vibrations tens of kilometers from the railway. This potentially allows train noise to be used as a source in seismic interference techniques.
This data processing method uses disturbances generated by an extended source and recorded by two spaced-apart detectors. As a result, it is possible to find out the properties of the Earth's crust, as if the sources of disturbances were located at the location of the receivers. Previously, using seismic interference, it was possible to restore only the low-frequency component of the oscillations (from 0.1 to 1 hertz), but the extraction of the train signal from the noise can be used to determine the high-frequency part, which is most sensitive to the propagation velocity.
System operation diagram. Two detectors (red triangles) register vibrations from the train (on the right), which makes it possible to restore the properties of the crust between the receivers and, in particular, to determine the jump in the wave velocity into the regional fault.
As a test site, the authors of the new work used an area near the San Jacinto Fault in California. According to the scientists' calculations, the passage of 25 heavy freight trains per day is energetically equivalent to an earthquake of magnitude 2, 2, which is enough to restore the signal of compression waves (P-waves), probing the crust four kilometers inward. This covers the upper area of seismic activity, where many earthquakes are born. However, a one percent change in speed over the entire distance between the detectors can be detected with an accuracy of no worse than 0.05 seconds, that is, a quarter of a period for waves with a frequency of 5 hertz. Therefore, high quality equipment is required for successful work.
The researchers are going to significantly expand the coverage area of the detectors, since California has a fairly extensive rail network. The authors' estimates show that such a system can be deployed at least over almost the entire territory of the San Andreas Fault System. Potentially, by increasing the sensitivity, it will also be possible to exploit the noise of trucks and cars, which will drastically increase the area suitable for monitoring.
Earlier, geologists saw the "emergence" of the source of a large earthquake, and with the help of machine learning it was possible to see the cyclicity of earthquakes from the work of geothermal stations. Also recently, new evidence has emerged that geological activity on the moon continues to this day.
