An improved method for hydrofracture induced microseismic event detection and phase picking

Abstract

The ability to detect small microearthquakes and identify their P and S phase arrivals is a key issue in hydrofracture downhole monitoring because of the low signal-to-noise ratios. We apply an array-based waveform correlation approach (matched filter) to improve the detectability of small magnitude events with mechanisms and locations similar to a nearby master event. After detecting the weak events, we use a transformed spectrogram method to identify the phase arrivals. We have tested the technique on a downhole monitoring dataset of the microseismic events induced by hydraulic fracturing. We show that, for this case, one event with a signal-to-noise ratio around 6dB, which is barely detectable using an array-stacked short-time average/long-time average (STA/LTA) detector under a reasonable false alarm rate, is readily detected on the array-stacked correlation traces. The transformed spectrogram analysis of the detected events improves P and S phase picking.