SCEC Award Number 20018 View PDF
Proposal Category Individual Proposal (Integration and Theory)
Proposal Title Using deep learning to probe the spatiotemporal evolution and fault structure of the four-year Cahuilla, California earthquake swarm
Investigator(s)
Name Organization
Zachary Ross California Institute of Technology
Other Participants
SCEC Priorities 3a, 3f, 2c SCEC Groups Seismology, EFP, CS
Report Due Date 03/15/2021 Date Report Submitted 03/13/2021
Project Abstract
 The vibrant evolutionary patterns made by earthquake swarms are incompatible with standard, effectively two-dimensional models for general fault architecture. We leverage advances in earthquake monitoring with a deep learning algorithm to image a fault zone hosting a four-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 three-dimensional variations in fault architecture.
Intellectual Merit This project advances our understanding of the physical processes responsible for driving earthquake sequence. It also advances our understanding of the geometry of fault zones at seismogenic depths, and illustrates how the mechanical properties of fault zones can affect the evolution of a sequence.
Broader Impacts The project contributed to the training of a postdoctoral scholar in machine learning and earthquake monitoring. The SCSN found out about this earthquake swarm from an email sent by a citizen scientist who lived nearby and was concerned about what was happening here. We now understand this sequence well, and in fact, we shared a copy of the paper on this sequence with the individual once published to show that their inquiry led to an improved understanding of this process.
Exemplary Figure Figure 2. Spatiotemporal evolution of the sequence. Fluids are naturally injected into the base of the fault zone and diffuse within it through channels (black arrows). A) Map view of seismicity evolution, with events color-coded by occurrence time. B) Fault-parallel cross-section along Z-Z', note the inferred permeability barrier and injection point. C) Absolute distance of seismicity relative to injection point in B projected into along-strike and along-dip components.