Abstract
Improving the capability of seismic network to detect weak seismic events is one of the timeless challenges in seismology: the greater is the number of detected and locatable seismic events, the greater insights on the mechanisms responsible for seismic activation may be gained. Here we implement and apply a single-station template matching algorithm to detect events belonging to the fluid-injection induced seismicity cluster located in the High Agri Valley, Southern Italy, using the continuous seismic data stream of the closest station of the INSIEME network. To take into account the diversity of waveforms, albeit belonging to the same seismic cluster, eight different master templates were adopted. Afterwards, using all the stations of the network, we provide a seismic catalogue consisting of 196 located earthquakes, in the magnitude range − 1.2 ≤ Ml ≤ 1.2, with a completeness magnitude Mc = − 0.5 ± 0.1. This rich seismic catalogue allows us to describe the damage zone of a SW dipping fault, characterized by a variety of fractures critically stressed in the dip range between ~ 45° and ~ 75°. The time-evolution of seismicity clearly shows seismic swarm distribution characteristics with many events of similar magnitude, and the seismicity well correlates with injection operational parameters (i.e. injected volumes and injection pressures).
Highlights
During the last 20 years a variety of conventional and unconventional underground energy projects have been developed to meet the growing energy demand due to the economic development and the rapid increase of world population
The detection of events was performed by cross-correlating 8 master events and continuous data acquired by INS1 station, the nearest station to the analyzed seismicity cluster and the only one installed in a borehole at a depth of 50 m, equipped with a 120 s–100 Hz broadband sensor which provides good quality data with low background noise level[18]
Our method for detecting weak microseismic events is based on a single-station template matching algorithm which evaluates the waveform similarity of the continuous data stream with selected master events through the cross-correlation coefficient XC
Summary
During the last 20 years a variety of conventional and unconventional underground energy projects have been developed to meet the growing energy demand due to the economic development and the rapid increase of world population. In addition to the high density of stations, the main advantages of modern microseismic monitoring networks are: (1) the use of high quality sensors with a large dynamic range placed in shallow or deep boreholes which reduces the background noise level[18,19,20]; (2) the availability of continuous data streams from each seismic station allowing for the real-time or off-line application of advanced d etection[21,22,23] and location[24,25,26,27,28,29,30] techniques, which results in decreased magnitude of completeness and generation of massive microseismic catalogues of accurate located events. The decrease of the completeness magnitude allows us to better study the spatiotemporal evolution of the induced seismicity cluster and its relation with injection operations in the investigation period from 2016-10-12 to 2018-08-31 (about 2 years), when both seismicity recordings and fluid-injection data are available
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