Preprints
https://doi.org/10.5194/egusphere-2024-2025
https://doi.org/10.5194/egusphere-2024-2025
10 Jul 2024
 | 10 Jul 2024
Status: this preprint is open for discussion.

Analysis of Borehole Strain Anomalies Before the 2017 Jiuzhaigou Ms7.0 Earthquake Based on Graph Neural Network

Chenyang Li, Changfeng Qin, Jie Zhang, Yu Duan, and Chengquan Chi

Abstract. On August 8, 2017, a strong magnitude 7.0 earthquake occurred in Jiuzhaigou, Sichuan Province, China. To assess pre-earthquake anomalies, we utilized variational mode decomposition to preprocess borehole strain observation data and combined it with a graph wavenet graph neural network model to process data from multiple stations. We obtained one-year data from four stations near the epicenter as the training dataset and data from January 1 to August 10, 2017, as the test dataset. For the prediction results of the variational mode decomposition-graph wavenet model, the anomalous days were extracted using statistical methods, and the results of anomalous day accumulation at multiple stations showed that an increase in the number of anomalous days occurred 15–32 days before the earthquake. The acceleration effect of anomalous accumulation was most obvious in the 20-day period before the earthquake, and an increase in the number of anomalous days also occurred in the one to three days post-earthquake. We tentatively deduce that the pre-earthquake anomalies are caused by the diffusion of strain energy near the epicenter during the accumulation process, which can be used as a signal of pro-seismic anomalies, whereas the post-earthquake anomalies are caused by the frequent occurrence of aftershocks.

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Chenyang Li, Changfeng Qin, Jie Zhang, Yu Duan, and Chengquan Chi

Status: open (until 21 Aug 2024)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
Chenyang Li, Changfeng Qin, Jie Zhang, Yu Duan, and Chengquan Chi
Chenyang Li, Changfeng Qin, Jie Zhang, Yu Duan, and Chengquan Chi

Viewed

Total article views: 83 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
55 18 10 83 3 5
  • HTML: 55
  • PDF: 18
  • XML: 10
  • Total: 83
  • BibTeX: 3
  • EndNote: 5
Views and downloads (calculated since 10 Jul 2024)
Cumulative views and downloads (calculated since 10 Jul 2024)

Viewed (geographical distribution)

Total article views: 105 (including HTML, PDF, and XML) Thereof 105 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 24 Jul 2024
Download
Short summary
In this study, we advance the field of earthquake prediction by introducing a pre-seismic anomaly extraction method based on the structure of graph-wave network, which reveals the temporal correlation and spatial correlation of the strain observation data from different boreholes prior to the occurrence of an earthquake event.