Characterizing North Texas Seismicity with a High Density Network of Exploration Seismic Reflection Recorders

Abstract:

A series of low magnitude earthquakes in North Texas near Azle, Texas began 5-Nov 2013 and continues to the present. By 3-Jan 2014, hypocenters based on a temporary local network were sufficiently well defined to plan an experiment using a dense network near the epicenters. On 25-Feb 2014, NodalSeismic in cooperation with Southern Methodist University, installed and operated 130 vertical 10 Hz recorders distributed along three lines within a few km of the epicenters and collected 10 days of continuous seismic recording at 500 samples/second. Data was converted from SEGD to standard earthquake seismological formats (SEED) for processing.

During the time of the high density recording, relatively few events in the Azle area were detected by the 12 station local network; however, correlation processing on the dense network detected over 100 events. In addition regional events from local quarries as well as a teleseism were well recorded. One of the 10Hz recorders was within 50m of a 1 Hz vertical seismometer, providing the ability to evaluate the utility of the high frequency geophones for recording broader band signals. By comparing catalogs from the local network with detection lists from the high density network, the detection threshold for the augmented network is determined. Delta time offsets for the teleseismic signal may be used to determine relative station corrections (static offsets) prior to fitting classical hyperbola to a velocity model and to estimate epicenters. Comparison between dense network location results and results using standard techniques on the 12 station local network provides an assessment of the utility of this high density technique to quickly evaluate areas where induced seismicity is suspected. Finally, the method provides an opportunity to compare background noise levels between the rapidly installed low cost exploration systems and the more carefully deployed local network.