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A Frequency-Domain-Based Algorithm for Detecting Induced Seismicity Using Dense Surface N-Arrays

Detecting induced seismicity using surface arrays located near injection wells is challenging mainly due to the noise introduced by the anthropogenic activity. Additionally, induced events with magnitudes M<0 typically have small amplitudes and short durations (~ 0.5-1 s), which complicate event detection in the time-domain and inflate false detections. To overcome these issues, we introduce a new frequency-domain-based algorithm for detecting induced events with small magnitudes using dense nodal arrays. Our proposed method takes advantage of the high energy carried by S waves, the known location of the injections and the geometry of the array. The processing stages involved in event detection are: (1) Preprocess the raw data by filtering, removing the mean and linear trend and rotating the horizontal components to the direction of the injection well, (2) Compute 2-hr long spectrograms for each station, (3) Sum the amplitudes for a given frequency range and return the envelope of the stacked amplitude - time series across the array and (4) Run a sliding window and declare detections above a threshold. We apply the new method during an injection phase at the Utah Frontier Observatory for Research in Geothermal Energy (FORGE) in southcentral Utah, where a dense circular array consisting of 151 5-Hz three component nodal geophones over a 5 km aperture was in operation. The geophones were distributed in five concentric rings centered around well 58-32 and were recording continuously at 1 kHz, during the different injection stages. Event detections derived by the new method are compared to the catalog provided by Schlumberger compiled using a deep borehole 12-level geophone string.

Presenting Author: Kristine Pankow

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