Original title: “What? Is the magma network under the volcano like this? “
A long time ago, we introduced the basic knowledge of volcanoes, the classification of volcanoes, the formation of volcanoes, and the distribution of volcanoes. Presumably everyone has a certain understanding of volcanoes. If you don’t have a certain understanding, go out and turn right to read the previous tweets! (guidance 👉After the Tonga volcano erupted, you should know the volcano story! (one),After the Tonga volcano erupted, you should know the volcano story! (two)) Volcanoes distributed all over the world have more or less become famous tourist attractions, such as Mount Fuji in Japan, Tianchi Lake in Changbai Mountain in China, and Hawaii, the Pearl of the Pacific in the United States. Today we will talk about this famous vacation spot, tourist attraction, and also a hotspot of earth science research (true hot spot, related to the mantle plume).
Hawaii is located in the middle of the Pacific Ocean and consists of 132 islands. These islands were formed by volcanic eruptions, so volcanic eruptions in the ocean can make land. As early as the last century, after the plate theory was proposed, it was discovered that the island of Hawaii is not on the edge of the plate, so why is there such a wide range of volcano distribution? That’s when industry patriarch John Tuzo Wilson came up with a brilliant idea, the hot spot theory, which states that volcanoes can form from a single stationary plume inside a plate, even if it’s not on a plate boundary. In 2003, researchers discovered that the hotspots are actually not fixed, but moving, which means that the current distribution shape of Hawaii Island is caused by the movement of hotspots. The research on Hawaii Island has never stopped, and the research has become more and more detailed and in-depth.
Not long ago, Science published an article titled: The magmatic web beneath Hawai’i. The titles of top journal articles are always so concise and powerful, meaning the magmatic web beneath Hawaii. Due to the limitations of technical means, people cannot directly see the underground structure. You can’t slice the earth, right? This work may only be done by the “Three-body Man”. With the current scientific level of our human beings, it is still impossible. After all, even if the well is drilled, it will be at most 12km, and the crust has not been drilled, let alone the study of the mantle. Therefore, more indirect research techniques are developed, and the earth CT technique is used the most—earthquake! There are quite a lot of popular science about earthquakes, and you can search for them yourself. We know that seismic information can be used to study the structure of the Earth’s interior, even its core. Therefore, more seismic data can help us obtain a finer picture of the subsurface structure. There are more analysis directions, such as obtaining the underground seismic wave velocity structure for research, and using earthquake location data for research. Both are powerful seismological tools for studying underground structures, and they focus on different directions. Velocity structure emphasizes overall structural analysis, such as which low-velocity body corresponds to which structure, which high-speed body corresponds to which structure; and earthquake location It is easier to judge certain boundaries or places where tectonic activity is stronger, such as the Benioff zones (Benioff zones), which are the structures of subducting slabs.
Since seismic-location data can identify more structurally active areas, these magma networks under volcanoes must be one of them. The article mentioned above is to use the earthquake location data to identify and judge the magma network, but it needs to add some other ingredients, and this ingredient is the deep learning algorithm. AI algorithms such as deep learning are now widely used in various industries and fields, such as driverless cars, etc. In the field of earth sciences, there has also been a blowout increase in the number of related papers in recent years. How specific AI algorithms can help the field of earth sciences, we will talk about it separately in other follow-up tweets.
Now let’s look at the magma network in Hawaii. The central conclusion of the article is that the earthquake location data obtained through deep learning algorithms, etc., reconstructed a huge rock bed in the mantle, with a scale of 15km long, and through the narrow and long seismic activity zone (25km) and Volcanoes are connected, and they will also be connected to some rock beds in the shallow part. These structures fully confirm that this huge rock bed in the mantle is the hub of underground magma transportation, further confirming the connectivity of the magma network.
As for how to do it, let’s roughly describe: First, all the positioning data started after the collapse of the Kīlauea crater (Kīlauea) in 2018, and the total amount of data reached 200,000. Many, thanks to the advancement of seismological observation methods (the extensive deployment of seismic stations and mobile stations). Seismic activity has grown stronger since the Kilauea crater collapsed and erupted. Using this database, the researchers processed it through deep learning and obtained a fine-grained catalog of earthquakes (more fine-grained in space and time). A finer earthquake catalog is the basis for structural analysis. Such an earthquake catalog will be more accurate in space and time, and it will also be able to invert the spatial and temporal evolution of seismic activity.
After studying and analyzing the spatial distribution and temporal evolution of the data, the researchers identified the structure of Pāhala, which is a huge rock bed structure in the mantle. In the 3.5 years since 2018, a total of 192,000 earthquakes have been recorded in this region, which is a staggering number. After cluster analysis, the researchers found that it is mainly a discrete layered near-horizontal structure, with an overall horizontal extension of 17 kilometers and a westward inclination of about 25°. The thickness of each cluster can reach 300m. In terms of time evolution, the active time of each cluster is also obviously different, showing the regularity of its magma activity.
Figure AB on the left shows the earthquake location results and clustering results of Pāhala, and Figure ABCD on the right shows the time evolution law of earthquake results for the four five-pointed star regions in the left picture (Wilding et al., 2022)
The researchers fine-tuned the seismic data by combining deep learning algorithms, and used this to finely image the subsurface magma network of the Hawaiian volcano, and obtained a clear magma network structure. This is an exceptionally wonderful research article , It also promotes human beings’ further understanding of the activity of volcanoes. It seems that even as bugs, we humans are bugs that think actively! (By the way, everyone, go watch the Three-Body Problem TV series, haha)
Tatsumi Y., Eggins S. Subduction zone magmatism. Cambridge: Blackwell Science, Inc. 1995. 1-49
Wilding, JD, Zhu, W., Ross, ZE, & Jackson, JM (2022). The magnetic web beneath Hawai ‘i. Science, eade5755.
This article comes from the WeChat public account:Stone Science Studio (ID: Dr__Stone)Author: Xingyu
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