Using Cross-Correlation Methods to Characterize Earthquakes Associated with the Socorro Magma Body

The Socorro Magma Body (SMB) is a thin, sill-like body that exists at 19-km depth within the Rio Grande Rift in central New Mexico. It is estimated to cover 3400 km², making it one of the largest observed continental mid-crustal magma bodies by areal extent. The SMB is associated with regional uplift and concentrated shallow seismicity, including early 20^th century M 5.5-6 events and recent small earthquakes (M 3 to -1). Seismicity has been monitored with a variety of long-term broadband networks and short-term nodal instruments over the past several decades, including a dense nodal deployment in February 2015 situated over the region of maximum uplift. However, routine catalogs are incomplete at low magnitudes (M < 2), have not been relocated nor interpreted in terms of newer models of the SMB or its emplacement and history. In this study we aim to exploit all available seismic network data in a cross-correlation framework developed at Lawrence Livermore National Laboratory to detect and cluster events. We begin by running data from 9 local SC network stations through the framework from the years 2003 to 2018, using an existing bulletin of over 3,000 local earthquakes and explosions as templates. The most prolific clusters formed at individual stations contain a few hundred detections, which we believe will correspond to the addition of a few hundred events to the catalog. A correlation-based stack-picking tool is also developed to create a semi-automatic phase picker that also returns time-of-day and day-of-week statistics for each cluster to aid in event classification. Phase picks are used with BayesLoc, a Bayesian, multiple-event location algorithm to give initial locations of the newly detected events. LLNL-ABS-755164.