Earthquakes are indeed triggered by fault dislocations, but whether this process alone can produce the actual earthquake energy released by the mainshock has long been questioned. Therefore, exploring the true source of energy that causes earthquakes after the first motion is necessary. Based on analyses of the waveforms and ray paths at seismic stations close to the epicenter, it is considered that strong earthquake vibrations may not be caused by S-waves. It is also proposed that the reservoirs in sedimentary strata contain large amounts of high-pressure fluids, whose pressures can be released under certain conditions; this release of pressure may be an important component of the main earthquake energy. When a natural fault ruptures and penetrates a reservoir with a large area, the elastic energy produced by the release of pressure can reach the energy released by an earthquake of magnitude 8.0. Artificial engineering activities can lead to small-scale fluid pressure release phenomena, such as blowouts during drilling and earthquakes induced by hydraulic fracturing. Much direct and indirect evidence, such as the characteristics of seismic waves in the time and frequency domains recorded during the Wenchuan earthquake, explosion phenomena observed on the ground and cores obtained by scientific drilling, indicates the possibility of such energy release. We propose that seismicity can be divided into three stages: the microfracturing stage, in which there is fluid activity and can produce an electrokinetic effect; the significant fracturing stage after the initial movement; and the strong earthquake stage caused by fluid pressure release.
Low-magnitude seismic activity between the Kamchatka July 20 and July 29, 2025, earthquakes. Spatio-temporal evolution recovered using waveform cross-correlation
Spatio-temporal evolution of low-magnitude seismicity before the May 24, 2013, Sea of Okhotsk earthquake recovered by waveform cross correlation. Is it an earthquake prediction case?
Relative relocation of earthquakes without a predefined velocity model: an example from a peculiar seismic cluster on Katla volcano's south-flank (Iceland)
Prediction of the Kamchatka July 29, 2025, earthquake by the evolution of low-magnitude seismicity recovered using waveform cross-correlation at IMS seismic arrays
Recovery of low-magnitude seismic events before the July 29, 2025, Kamchatka megathrust earthquake using waveform cross-correlation enhanced by the addition of stochastic noise
Seismic-phase detection using multiple deep learning models for global and local representations of waveforms
Earthquake Research Institute, The University of Tokyo（东京大学地震研究所）；Graduate School of Information Science and Technology, The University of Tokyo（东京大学信息科学与技术研究生院）
Rapid Earthquake-to-Tsunami Waveform Generation via Large-Scale Multi-GPU FFT Convolution Applied to the Cascadia Subduction Zone
Oden Institute for Computational Engineering；Sciences The University of Texas at Austin Austin, TX, USA；Sciences, Walker Department of Mechanical Engineering The University of Texas at Austin Austin, TX, USA
Effects of stochastic and natural seismic noise on the performance of waveform cross-correlation used to recover low-magnitude seismicity prior to the July 29, 2025, Kamchatka earthquake
Convergent representations of elastic-wave structure emerge across deliberately distinct seismic training routes
Institute of Geophysics, China Earthquake Administration（中国地震局地球物理研究所）；University of Chinese Academy of Sciences（中国科学院大学）；Laboratory of Seismology and Physics of Earth’s Interior, School of Earth and Space Sciences, University of Science and Technology of China（中国科学技术大学地球和空间科学学院地球内部地震学与物理学实验室）；Institute of Advanced Technology, University of Science and Technology of China（中国科学技术大学先进技术研究院）
Combining Deep Learning with Physics Based Features in Explosion-Earthquake Discrimination
Lawrence Livermore National Laboratory（劳伦斯利弗莫尔国家实验室）；University of New Mexico（新墨西哥大学）；Southern University of Science and Technology（南方科技大学）；University of Utah（犹他大学）
Attention network forecasts time-to-failure in laboratory shear experiments
Rice University（莱斯大学）；Pennsylvania State University（宾夕法尼亚州立大学）；Los Alamos National Laboratory（洛斯阿拉莫斯国家实验室）；University of Nevada, Reno（内华达大学雷诺分校）；Sapienza Universitá di Roma（罗马一大（萨皮恩扎大学））
Broadband Ground-Motion Synthesis by Conditioning Denoising Diffusion Models on Low-Frequency Waveforms
Swiss Seismological Service (SED), ETH Zürich, Switzerland（瑞士地震服务处（SED），苏黎世联邦理工学院）；Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, IRD, Univ. Gustave Eiffel, ISTerre, Grenoble, France（格勒诺布尔阿尔卑斯大学，萨瓦-蒙布朗大学，法国国家科学研究中心，法国研究与可持续发展研究所，巴黎土木工程师大学，ISTerre，格勒诺布尔，法国）；Swiss Data Science Center (SDSC), ETH Zürich, Switzerland（瑞士数据中心（SDSC），苏黎世联邦理工学院）；Earth and Planetary Science Department, ETH Zürich, Switzerland（地球与行星科学系，苏黎世联邦理工学院）
