The importance of the new discovery is that it leverages existing optical fiber networks. These are already of sufficient sensitivity as to detect even very slight seismic events. The data collected can be used to show earthquake direction and magnitude.
These various networks can be put together to create an earthquake-sensing observatory composed of a ‘billion’ sensors, with data collected and tracked in ‘real time’. This would supply superior data compared with traditional seismic sensors.
In addition, the cost of constructing such a network would be considerably lower than using traditional sensors since the network already exists. All that is needed is the fitting of a device called a laser interrogator.
OptaSense
This device has been developed by the company OptaSense, and it simply needs to be positioned at one end of an optical fiber. This concept is based on research undertaken by Professor Biondo Biondi.
The laser interrogator works by sending pulses of laser light into the fiber. The device then monitors the backscattered light. If there are shifts in the timing of the backscatter, this information is correlated against the displacements of the fiber as it stretches or contracts. The displacement occurs when the earth moves, as during an earthquake.
One single laser interrogator can cover around 40 kilometers of fiber. This gives the equivalency of assessing a virtual sensor every couple of meters and allows for continual assessment.
Tracking tremors
This has been established through a proof-of-concept study where scientists recorded seismic tremors in a 3-mile loop of optical fiber located underneath the Stanford University campus. Data has been collected since September 2016, with over 800 events recorded to date. This includes detecting two small local earthquakes, which had magnitudes of 1.6 and 1.8.
Moreover, with the sensitivity, the network can differentiate between the two different types of waves that move through the planet. These are: P waves, which are less damaging and which arrive much earlier; and more powerful S waves. Based on the data analysis, the approach is likely to be rolled out on a wider scale.
