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Absolute Relocations of a Machine Learning Catalog of the Utah Magna Earthquake Sequence Using Nonlinloc-Ssst-Coherence

Description: 

On March 18, 2020, a magnitude 5.7 earthquake hit the Salt Lake Valley in the state of Utah, USA. This mainshock triggered approximately 2600 locatable aftershocks over the following 18 months, a small but significant number of which were felt by the local population. Using a dense geophone deployment and machine learning (ML), an additional several thousand events were detected and located. Currently, both the mainshock and the majority of the aftershocks are suspected to have occurred on or near a deeper portion of the Salt Lake Segment of the Wasatch Fault, part of a large range-bounding fault system thought to be capable of generating a Mw 7.2 earthquake. However, a small subset of aftershocks may have occurred on a portion of the more steeply, eastern dipping and poorly understood West Valley Fault. Unfortunately, the catalog locations and lack of resulting focal mechanisms for this subset of aftershocks provides only a crude constraint on the true fault structure. To better illuminate structure, we relocate the UUSS catalog and larger ML generated catalog using: 1) NonLinLoc, a nonlinear location algorithm, 2) source-specific station terms (SSST), and 3) waveform coherence. We use the same regional 1D velocity model as is used for routine location in Utah for non-basin stations and a modified version of the model that includes a low velocity layer for stations located in the Salt Lake Valley basin. The locations achieved in this study suggest that the eastern events may have occurred on the Wasatch Fault, and indicate distinct, shallowly dipping, near-parallel planes in the seismicity near the mainshock, suggestive of multiple slip surfaces. These findings have direct implications to seismic hazard in the Salt Lake City metropolitan area. This research was funded by the National Nuclear Security Administration, Defense Nuclear Nonproliferation Research and Development (NNSA DNN R&D). The authors acknowledge important interdisciplinary collaboration with scientists and engineers from LANL, LLNL, MSTS, PNNL, and SNL. SNL is managed and operated by NTESS under DOE NNSA contract DE-NA0003525.

Session: It’s All About Relocation, Relocation, Relocation [Poster]

Type: Poster

Date: 4/20/2023

Presentation Time: 08:00 AM (local time)

Presenting Author: Daniel Wells

Student Presenter: Yes

Invited Presentation: 

Authors