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Scientists obtain detailed maps of earthquake-triggering high-pressure subsurface fluids

Researchers in Japan and Taiwan have captured three-dimensional images of an entire geothermal system deep in the Earth’s crust for the first time. By mapping the underground distribution of phenomena such as fracture zones and phase transitions associated with seismic activity, they say their work could lead to improvements in earthquake early warning models. It could also help researchers develop next-generation versions of geothermal power – a technology that study leader Takeshi Tsuji of the University of Tokyo says has enormous potential for clean, large-scale energy production.

“With a clear three-dimensional image of where supercritical fluids are located and how they move, we can identify promising drilling targets and design safer and more efficient development plans,” Tsuji says. “This could have direct implications for expanding geothermal power generation, reducing dependence on fossil fuels, and contributing to carbon neutrality and energy security in Japan and globally.”

In their study, Tsuji and colleagues focused on a region known as the brittle-ductile transition zone, which is where rocks go from being seismically active to mostly inactive. This zone is important for understanding volcanic activity and geothermal processes because it lies near an impermeable sealing band that allows fluids such as water to accumulate in a high-pressure, supercritical state. When these fluids undergo phase transitions, earthquakes may follow. However, such fluids could also produce more geothermal energy than conventional systems. Identifying their location is therefore important for this reason, too.

A high-resolution “digital map”

Many previous electromagnetic and magnetotelluric surveys suffered from low spatial resolution and were limited to regions relatively close to the Earth’s surface. In contrast, the techniques used in the latest study enabled Tsuji and colleagues to create a clear high-resolution “digital map” of deep geothermal reservoirs – something that has never been achieved before.

To make their map, the researchers used three-dimensional multichannel seismic surveys to image geothermal structures in the Kuju volcanic group, which is located on the Japanese island of Kyushu. They then analysed these images using a method they developed known as extended Common Reflection Surface (CRS) stacking. This allowed them to visualize deeper underground features such as magma-related structures, fracture-controlled fluid pathways and rock layers that “seal in” supercritical fluids.

“In addition to this, we applied advanced seismic tomography and machine-learning based analyses to determine the seismic velocity of specific structures and earthquake mechanisms with high accuracy,” explains Tsuji. “It was this integrated approach that allowed us to image a deep geothermal system in unprecedented detail.” He adds that the new technique is also better suited to mountainous geothermal regions where limited road access makes it hard to deploy the seismic sources and receivers used in conventional surveys.

A promising site for future supercritical geothermal energy production

Tsuji and colleagues chose to study the Kuju area because it is home to several volcanoes that were active roughly 1600 years ago and have erupted intermittently in recent years. The region also hosts two major geothermal power plants, Hatchobaru and Otake. The former has a capacity of 110 MW and is the largest geothermal facility in Japan.

The heat source for both plants is thought to be located beneath Mt Kuroiwa and Mt Sensui, and the region is considered a promising site for supercritical geothermal energy production. Its geothermal reservoir appears to consist of water that initially fell as precipitation (so-called meteoric water) and was heated underground before migrating westward through the fault system. Until now, though, no detailed images of the magmatic structures and fluid pathways had been obtained.

Tsuji says he has long wondered why geothermal power is not more widely used in Japan, despite the country’s abundant volcanic and thermal resources. “Our results now provide the scientific and technical foundation for next-generation supercritical geothermal power,” he tells Physics World.

The researchers now plan to try out their technique using portable seismic sources and sensors deployed in mountainous areas (not just along roads) to image the shallower parts of geothermal systems in greater detail as well. “We also plan to extend our surveys to other geothermal fields to test the general applicability of our method,” Tsuji says. “Ultimately, our goal is to provide a reliable scientific basis for the large-scale deployment of supercritical geothermal power as a sustainable energy source.”

The present work is detailed in Communications Earth & Environment.

The post Scientists obtain detailed maps of earthquake-triggering high-pressure subsurface fluids appeared first on Physics World.

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Researchers map the unrest in the Vulcano volcano

The isle of Vulcano is a part of the central volcanic ridge of the Aeolian archipelago on the Tyrrhenian Sea in southern Italy. Over the course of its history, Vulcano has undergone multiple explosive eruptions, with the last one thought to have occurred around 1888–1890. However, there is an active hydrothermal system under Vulcano that has shown evidence of intermittent magma and gas flows since 2021 – a sign that the volcano has been in a state of unrest.

During unrest, the volcanic risk increases significantly – and the summer months on the island currently attract a lot of tourists that might be at risk, even from minor eruptive events or episodes of increased degassing. To examine why this unrest has occurred, researchers from the University of Geneva have collaborated with the National Institute of Geophysics and Volcanology (INGV) in Italy to recreate a 3D model of the interior of the volcano on Vulcano, using a combination of nodal seismic networks and artificial intelligence (AI).

Until now, few studies have examined the deep underground details of volcanoes, instead relying on looking at the outline of their internal structure. This is because the geological domains where eruptions nucleate are often inaccessible using airborne geophysical techniques, and onshore studies don’t penetrate far enough into the volcanic plumbing system to look at how the magma and hydrothermal fluids mix. Recent studies have shown the outline of the plumbing systems, but they’ve not had sufficient resolution to distinguish the magma from the hydrothermal system.

3D modelling of the volcano

To better understand what could have caused the 2021 Vulcano unrest, the researchers deployed a nodal network of 196 seismic sensors across Vulcano and Lipari (another island in the archipelago) to measure secondary seismic waves (S-waves) using a technique called seismic ambient noise tomography. S-waves propagate slowly as they pass through fluid-rich zones, which allows magma to be identified.

The researchers captured the S-wave data using the nodal sensor network and processed it with AI – using a deep neural network. This allowed the extensive seismic dispersion data to be quickly and automatically recovered, enabling generation of a 3D S-wave velocity model. The data were captured during the volcano’s early unrest’s phase, and the sensors recorded the natural ground vibrations over a period of one month. The model revealed the high-resolution tomography of the shallow part of a volcanic system in unrest, with the approach compared to taking an “X-ray” of the volcano.

“Our study shows that our end-to-end ambient noise tomography method works with an unprecedented resolution due to using dense nodal seismic networks,” says lead author Douglas Stumpp from the University of Geneva. “The use of deep neural networks allowed us to quickly and accurately measure enormous seismic dispersion data to provide near-real time monitoring.”

The model showed that there was no new magma body between Lipari and Vulcano within the first 2 km of the Earth’s crust, but it did reveal regions that could host cooling melts at the base of the hydrothermal system. These melts were proposed to be degassing melts that could easily release gas and brines if disturbed by an Earthquake – suggesting that tectonic fault dynamics may trigger volcanic unrest. It’s thought that the volcano might have released trapped fluids at depth after being perturbed by fault activity during the 2021 unrest.

Improving risk management

While this method doesn’t enable the researchers to predict when the eruption will happen, it provides a significant understanding into how the internal dynamics of volcanoes work during periods of unrest. The use of AI enables rapid processing of large amounts of data, so in the future, the approach could be used as an early warning system by analysing the behaviour of the volcano as it unfolds.

In theory, this could help to design dynamic evacuation plans based on the direct real-time behaviour of the volcano, which would potentially save lives. The researchers state that this could take some time to develop due to the technical challenge of processing such massive volumes of data in real time – but they note that this is now more feasible thanks to machine learning and deep learning.

When asked about how the researchers plan to further develop the research, Stumpp concludes that “our study paves the ground for 4D ambient noise tomography monitoring – three dimensions of space and one dimension of time. However, I believe permanent and maintained seismic nodal networks with telemetric access to the data need to be implemented to achieve this goal”.

The research is published in Nature Communications.

The post Researchers map the unrest in the Vulcano volcano appeared first on Physics World.

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Android phone network makes an effective early warning system for earthquakes

The global network of Android smartphones makes a useful earthquake early warning system, giving many users precious seconds to act before the shaking starts. These findings, which come from researchers at Android’s parent organization Google, are based on a three-year-long study involving millions of phones in 98 countries. According to the researchers, the network’s capabilities could be especially useful in areas that lack established early warning systems.

By using Android smartphones, which make up 70% of smartphones worldwide, the Android Earthquake Alert (AEA) system can help provide life-saving warnings in many places around the globe,” says study co-leader Richard Allen, a visiting faculty researcher at Google who directs the Berkeley Seismological Laboratory at the University of California, Berkeley, US.

Traditional earthquake early warning systems use networks of seismic sensors expressly designed for this purpose. First implemented in Mexico and Japan, and now also deployed in Taiwan, South Korea, the US, Israel, Costa Rica and Canada, they rapidly detect earthquakes in areas close to the epicentre and issue warnings across the affected region. Even a few seconds of warning can be useful, Allen explains, because it enables people to take protective actions such as the “drop, cover and hold on” (DCHO) sequence recommended in most countries.

Building such seismic networks is expensive, and many earthquake-prone regions do not have them. What they do have, however, is smartphones. Most such devices contain built-in accelerometers, and as their popularity soared in the 2010s, seismic scientists began exploring ways of using them to detect earthquakes. “Although the accelerometers in these phones are less sensitive than the permanent instruments used in traditional seismic networks, they can still detect tremors during strong earthquakes,” Allen tells Physics World.

A smartphone-based warning system

By the late 2010s, several teams had developed smartphone apps that could sense earthquakes when they happen, with early examples including Mexico’s SkyAlert and Berkeley’s ShakeAlert. The latest study takes this work a step further. “By using the accelerometers in a network of smartphones like a seismic array, we are now able to provide warnings in some parts of the world where they didn’t exist before and are most needed,” Allen explains.

Working with study co-leader Marc Stogaitis, a principal software engineer at Android, Allen and colleagues tested the AEA system between 2021 and 2024. During this period, the app detected an average of 312 earthquakes a month, with magnitudes ranging from 1.9 to 7.8 (corresponding to events in Japan and Türkiye, respectively).

Detecting earthquakes with smartphones

Animation showing phones detecting shaking as a magnitude 6.2 earthquake in Türkiye progressed. Yellow dots are phones that detect shaking. The yellow circle is the P-wave’s estimated location and the red circle is for the S-wave. Note that phones can detect shaking for reasons other than an earthquake, and the system needs to handle this source of noise. This video has no sound. (Courtesy: Google)

For earthquakes of magnitude 4.5 or higher, the system sent “TakeAction” alerts to users. These alerts are designed to draw users’ attention immediately and prompt them to take protective actions such as DCHO. The system sent alerts of this type on average 60 times per month during the study period, for an average of 18 million individual alerts per month. The system also delivered lesser “BeAware” alerts to regions expected to experience a shaking intensity of 3 or 4.

To assess how effective these alerts were, the researchers used Google Search to collect voluntary feedback via user surveys. Between 5 February 2023 and 30 April 2024, 1 555 006 people responded to a survey after receiving alerts generated from an AEA detection. Their responses indicated that 85% of them did indeed experience shaking, with 36% receiving the alert before the ground began to move, 28% during and 23% after.

Graphic showing responses to survey on the effectiveness of the AEA and users' responses to alerts
Feeling the Earth move: Feedback from users who received an alert. A total of 1 555 006 responses to the user survey were collected over the period 5 February 2023 to 30 April 2024. During this time, alerts were issued for 1042 earthquakes detected by AEA. (Courtesy: Google)

Principles of operation

AEA works on the same principles of seismic wave propagation as traditional earthquake detection systems. When an Android smartphone is stationary, the system uses the output of its accelerometer to detect the type of sudden increase in acceleration that P and S waves in an earthquake would trigger. Once a phone detects such a pattern, it sends a message to Google servers with the acceleration information and an approximate location. The servers then search for candidate seismic sources that tally with this information.

“When a candidate earthquake source satisfies the observed data with a high enough confidence, an earthquake is declared and its magnitude, hypocentre and origin time are estimated based on the arrival time and amplitude of the P and S waves,” explains Stogaitis. “This detection capability is deployed as part of Google Play Services core system software, meaning it is on by default for most Android smartphones. As there are billions of Android phones around the world, this system provides an earthquake detection capability wherever there are people, in both wealthy and less-wealthy nations.”

In the future, Allen says that he and his colleagues hope to use the same information to generate other hazard-reducing tools. Maps of ground shaking, for example, could assist the emergency response after an earthquake.

For now, the researchers, who report their work in Science, are focused on improving the AEA system. “We are learning from earthquakes as they occur around the globe and the Android Earthquake Alerts system is helping to collect information about these natural disasters at a rapid rate,” says Allen. “We think that we can continue to improve both the quality of earthquake detections, and also improve on our strategies to deliver effective alerts.”

The post Android phone network makes an effective early warning system for earthquakes appeared first on Physics World.

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