Will China's AI Model Make a Seismic Change in Earthquake Prediction?

The model, called Deting, is based on one of the largest datasets of its kind in the world and can be used to identify earthquake signals, monitor seismic activity and support rapid responses to earthquakes, according to its developers.

“DiTing relies on massive amounts of data from China's earthquake monitoring network and advanced artificial intelligence technology and has greatly improved the accuracy and speed of seismic signal recognition,” Chen Shi, deputy director of the Institute of Geophysics under the China Earthquake Administration, said at a launch ceremony for the model in the southwestern city of Chengdu on Sunday.

03:16

China quake survivors face bitter cold amid supply shortages, homelessness

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The model's launch on Sunday coincided with the 48th anniversary of the devastating Tangshan earthquake in northern China, which killed at least 300,000 people and devastated the city.

The project is a joint effort between the National Supercomputing Center in Chengdu, the institute, and Tsinghua University.

It takes its name from a divine beast in Chinese Buddhism that can pick up signals from all over the universe.

The supercomputing center said it was the first time seismic information on this scale had been collected to train AI in China, overcoming the limitations of traditional or smaller-scale models.

In total, the model can already evaluate 100 million parameters — or variables — to make predictions or decisions — and that total is expected to reach 1 billion in August, the state-run Science and Technology Daily quoted the center's head, Guo Li, as saying.

The more parameters a model has, the more detail it can capture in a dataset and the more it can improve overall performance.

The model was trained on seven years of seismic reports from the China Earthquake Networks Center, according to a paper from the research team published in Earthquake Science, the flagship journal of the Seismological Society of China.

02:22

Powerful earthquake hits northwest China, killing more than 100

Powerful earthquake hits northwest China, killing more than 100

The team said the information could be used as the basis for a range of earthquake-related research, setting a “standard for machine learning model development and data-driven seismic research” in areas such as earthquake detection, earthquake magnitude prediction, and ground motion forecasting.

DiTing and deep learning tools will greatly improve the detection of earthquake precursors and aftershocks, said Liu Xin, associate professor at the Department of Geosciences at the University of Hong Kong.

“We can use this DiTing dataset to train the next generation of earthquake denoising algorithms to enhance real-time earthquake monitoring in cities with high seismic risk, such as Chengdu, Wenchuan, Chongqing, and the well-known earthquake hotspots near the Tangshan-Beijing-Tianjin region,” said Liu, who was not involved in the DiTing study.

He said the DiTing model was based on more data than the STEAD model, a widely used seismic dataset developed by researchers at Stanford University in 2019.

While the STEAD database covered about 450,000 earthquakes between 1984 and 2018, the DiTing database used data covering 787,010 earthquakes from 2013 to 2020 in China.

The model could also be used in areas such as earthquake monitoring in mines, shale gas exploitation, underground space structure detection in urban areas, and underwater earthquake monitoring, the researchers said.

“More than 95 percent of the world's discovered oil and gas fields are mainly based on seismic exploration. DiTing can infer whether the subsurface contains oil and gas by learning the waveform characteristics of oil storage areas,” said Wang Jianbo, deputy director of the supercomputing center.

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