Revisiting the Ridgecrest aftershock catalog using a modified source-scanning algorithm applied to multiple dense local arrays

Eyal Shimony, Asaf Inbal, & Ariel Lellouch

Published September 11, 2022, SCEC Contribution #11890, 2022 SCEC Annual Meeting Poster #001 (PDF)

The two major Ridgecrest earthquakes of July 2019 were followed by numerous aftershocks. A temporary, spatially dense array was deployed over the summer of 2019 in order to monitor the aftershock activity. The array’s density and scale offer a unique opportunity to improve the estimations of the aftershocks’ locations and origin time through array-based techniques.
We develop and implement a modified Source-Scanning Algorithm (SSA) method to estimate absolute event locations in the presence of velocity model errors, commonly found around fault zones. We split the array into sub-arrays of clustered receivers, for which relative travel-times errors are smaller. We apply a conventional SSA using both P- and S-waves to each sub-array and combine the estimations using a probabilistic scheme to yield locations that are robust to velocity model errors. We also compute uncertainty estimations for the locations.
We apply the method to 688 aftershocks recorded by 197 short-period geophones deployed as part of the Ridgecrest dense array. The dense receiver deployment allows for the recording of spatially coherent seismic arrivals. We compare 339 locations to a relocated catalog built using a sparser regional array and the same 1-D velocity model. Generally, locations are consistent despite the different methodology and recorded data. We qualitatively compare location estimations using the alignment of time-shifted seismograms, utilizing the spatial coherency of the dense sub-arrays. Our locations yield, in most cases, better alignment, and are 2 km deeper on average. For events in the northern part of the study area, our locations are shifted to the north-east.
We discuss various potential causes for the differences between estimations and investigate the possibility of velocity-driven biases in our locations. We also attempt to approximate the scale of lateral velocity heterogeneity near the fault in the northern part of the study area. While our location method is tailored to the Ridgecrest dense array, it demonstrates that using dense arrays may help mitigate the effect of velocity model errors on absolute locations.

Key Words
source location, location methods, dense arrays

Citation
Shimony, E., Inbal, A., & Lellouch, A. (2022, 09). Revisiting the Ridgecrest aftershock catalog using a modified source-scanning algorithm applied to multiple dense local arrays. Poster Presentation at 2022 SCEC Annual Meeting.

Related Projects & Working Groups
Seismology