An Enhanced Earthquake Catalog for the 2020 Monte Cristo Range Sequence Derived from Machine Learning Processing of a Dense Aftershock Deployment

Maia Zhang, Daniel T. Trugman, Michelle Scalise, Eric Eckert, & Cleat Zeiler

Submitted September 7, 2025, SCEC Contribution #14786, 2025 SCEC Annual Meeting Poster #TBD

High resolution, near-source data can provide crucial information about earthquake processes, including enhanced detection of small earthquakes and improved source characterization due to minimal path attenuation. The Nevada National Security Site (NNSS) deployed 48 nodal geophones, known as LASSO (Large Array for Seismic Sensing and Observations) within hours (and meters) of the 2020 M_w 6.5, Monte Cristo Range earthquake (MCRE). With the data from this 3-month deployment, supplemented by regional seismic recordings from the Nevada Seismological Laboratory (NSL), we developed a machine learning workflow to generate a new, high resolution earthquake catalog for the MCRE aftershock sequence. Phase arrivals from the dense aftershock deployment improve detection capability several orders of magnitude beyond current published results while also highlighting key considerations for incorporating machine learning-based detection techniques at near source distances. We leverage the existing set of analyst-generated magnitudes to calculate and calibrate local magnitudes for newly detected events, ultimately producing a unique dataset with improved constraints on earthquake locations, magnitudes, and spacetime evolution of a highly active aftershock sequence, while laying the foundation for future analyses of near-source waveforms and event spectra.

Key Words
Machine Learning, Aftershocks, Near-Source

Citation
Zhang, M., Trugman, D. T., Scalise, M., Eckert, E., & Zeiler, C. (2025, 09). An Enhanced Earthquake Catalog for the 2020 Monte Cristo Range Sequence Derived from Machine Learning Processing of a Dense Aftershock Deployment. Poster Presentation at 2025 SCEC Annual Meeting.

Related Projects & Working Groups
Seismology