Seismological Laboratory, California Institute of Technology, Pasadena, CA, USA.
U.S. Geological Survey, Pasadena, CA, USA.
Science. 2020 Jun 19;368(6497):1357-1361. doi: 10.1126/science.abb0779.
The vibrant evolutionary patterns made by earthquake swarms are incompatible with standard, effectively two-dimensional (2D) models for general fault architecture. We leverage advances in earthquake monitoring with a deep-learning algorithm to image a fault zone hosting a 4-year-long swarm in southern California. We infer that fluids are naturally injected into the fault zone from below and diffuse through strike-parallel channels while triggering earthquakes. A permeability barrier initially limits up-dip swarm migration but ultimately is circumvented. This enables fluid migration within a shallower section of the fault with fundamentally different mechanical properties. Our observations provide high-resolution constraints on the processes by which swarms initiate, grow, and arrest. These findings illustrate how swarm evolution is strongly controlled by 3D variations in fault architecture.
地震群的活跃演化模式与通用断层结构的标准、有效二维（2D）模型不兼容。我们利用地震监测的进展，通过深度学习算法对加利福尼亚南部一个持续了 4 年的地震群所在的断层带进行成像。我们推断，流体从下方自然注入断层带，并在触发地震时通过与走向平行的通道扩散。渗透率障碍最初限制了向上的群集迁移，但最终被绕过。这使得流体能够在断层的一个浅层部分迁移，而该部分具有根本不同的力学性质。我们的观测结果对群集启动、增长和停止的过程提供了高分辨率的约束。这些发现说明了群集演化是如何受到断层结构三维变化的强烈控制的。
