A Dense Nodal 3C Deployment in the Cushing Fault Area, North Oklahoma
In November 2016, a M5 earthquake stuck the town of Cushing, the largest crude oil storage facility in the world. The earthquake caused significant building damages, especially some historic buildings. Preliminary analysis suggests that the earthquakes are mostly shallower than 3 km, which could cause higher shaking near the epicenter. To further understand the fault properties and monitor earthquake activities, 130 Fairfield 3C nodes were deployed in 5-by-5 km wide area on top of the fault system. The instruments recorded continuously from November 5 to December 15. Due to logistical and property right constraints, the instruments were deployed along county roads. The resulting survey grid comprises 4 E-W lines and 5 S-N lines with receiver spacings of 150 and 250 meters. In this study, we present preliminary results using the dense nodal array to analyze a M2.5 earthquake sequence that occurred close to the array in November 2019. We also apply interferometric ambient noise analysis and calculate teleseismic receiver functions to map the subsurface structure in the area.
Previous experiments proved the suitability of dense deployments with low-frequency geophones for deep earth studies, and we analyze our data for reflections from the outer and inner core. These phases can not only reveal information about the structure of the core but can also be used to image the shallow reflectivity structure below the recording array.
Presenting Author: Michael Behm
Additional Authors
Michael Behm michael.behm@ou.edu University of Oklahoma, Norman, Oklahoma, United States Presenting Author
Corresponding Author
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Xiaowei Chen xiaowei.chen@ou.edu University of Oklahoma, Norman, Oklahoma, United States |
Raymond Ng raymond.ng@ou.edu University of Oklahoma, Norman, Oklahoma, United States |
Zhuobo Wang zhuobo.wang-1@ou.edu University of Oklahoma, Norman, Oklahoma, United States |
A Dense Nodal 3C Deployment in the Cushing Fault Area, North Oklahoma
Category
Recent Development in Ultra-Dense Seismic Arrays With Nodes and Distributed Acoustic Sensing (DAS)