A Large-N Mixed Sensor Active + Passive Seismic Array near Sweetwater, TX

Abstract:

A collaborative high-density seismic survey using broadband and short period seismic sensors was conducted March 7 - April 30, 2014 near Sweetwater, TX. The objective of the survey was to use a combination of controlled source shot slices and passive seismic recordings recorded by multiple types of sensors with different bandwidths and sensitivities to image the subsurface. The broadband component of the survey consisted of 25 continuously recording seismic stations comprised of 20 Trillium Compact Posthole sensors from Nanometrics and 5 Polar Trillium 120PHQs from the IRIS/PASSCAL Instrument Center (PIC). The broadband stations also utilized 25 Centaur digitizers from Nanometrics as well as 25 polar quick deploy enclosures from the PIC. The broadband array was designed to maximize horizontal traveling seismic energy for surface wave analysis over the primary target area with sufficient offset for imaging objectives at depth. The short period component of the survey consisted of 2639 receiver locations using Zland nodes from NodalSeismic. The nodes are further divided into 3 sub-arrays: 1) outlier array 2) active source array 3) backbone array. The outlier array consisted of 25 continuously recording nodes distributed around the edge of the survey at a distance of ~5 km from the survey boundary, and provided valuable constraints to passive data analysis techniques at the edge of the survey boundary. The active source patch consisted of densely spaced nodes that were designed to record signals from a Vibroseis source truck for active source reflection processing and imaging. The backbone array consisted of 292 nodes that covered the entirety of the survey area to maximize the value of the passive data analysis. By utilizing continuous recording and smartly designed arrays for measuring local and regional earthquakes we can incorporate velocity information derived from passive data analysis into the active source processing workflow to produce a superior subsurface image. We also expect this data to be extremely valuable to the development of new concepts and techniques associated with large-N style surveys that eliminate spatial aliasing of the recorded wavefield. Furthermore, this dataset is open-source and available to download through the IRIS Data Management Center.