S058-08
Quantifying Rupture Characteristics of Microearthquakes in the Parkfield Region Using the Borehole High Resolution Seismic Network

Tuesday, 15 December 2020: 16:38
Virtual
Colin Pennington1, Xiaowei Chen1, Qimin Wu2, Jiewen Zhang1 and Rachel E Abercrombie3, (1)University of Oklahoma Norman Campus, School of Geosciences, Norman, OK, United States, (2)Lettis Consultants International Inc., Concord, CA, United States, (3)Boston University, Boston, MA, United States
Abstract:
It is well known that large earthquakes often exhibit significant rupture complexity such as well separated subevents and directivity. With improved recording and data processing techniques, small earthquakes have been found to exhibit rupture complexity as well (e.g., Abercrombie, 2014; Uchide & Imanishi 2016). Studying these small earthquakes offers an opportunity to better understand the possible causes of rupture complexities, and their relationship with fault properties. Most previous studies of small-to-moderate earthquake complexity focused on either very few earthquakes using both time and frequency domain approaches (e.g., Wu et al., 2019) or used only a single approach (e.g., Uchide & Imanishi, 2016; Wang et al., 2014). There has not been a study that combines time- and frequency-domain approaches to systematically analyze source complexity behaviors.

In this study, using the shallow borehole High Resolution Seismic Network, we combine both time- and frequency-domain approaches to investigate source complexity characteristics of small earthquakes (M<3) in the Parkfield area. The Parkfield area is chosen because it is a densely studied region with well documented structural and lithological features that the results of this work can be compared to. Using an empirical Green’s function (EGF) method, we quantify earthquake complexity based on: (1) the requirement of multiple slip pulses in source time function (STF) inversion; (2) the source spectra deviation from simple Brune-type source model. We then compare the consistency of event classification and spatial distributions of complexity observations between the two approaches. We find good agreement between the two approaches for M>2 events located within the borehole network, which have good resolution. For M>2.6 events, a majority of them are classified as complex by both methods. The spatial locations of complex and simple events tend to concentrate in regions with different creeping rates and fault structures. The consistency between time- and frequency-domain approaches suggests that the source complexity is mostly likely caused by multiple sub-events in the rupture process in this region. The spatial distribution pattern suggests that fault properties could influence earthquake rupture characteristics.