In the October issue of Bulletin of the Seismological Society of America, new work by a team that includes former ERL Associate Director Dr Michael Fehler, ERL/EAPS Research Scientist Dr Nori Nakata, and former ERL postdoc Dr Yusuke Mukuhira (now on the faculty of Tohoku University):
"The detection of microseismic events with low signal‐to‐noise ratios (SNRs) can expand the seismic catalog and provide opportunities for a deeper understanding of subsurface reservoir features. We propose a novel polarization analysis method for comprehensively detecting S‐wave arrival and P–S travel time of low‐SNR events from the particle motion of P and S waves in the time and frequency domain. In most circumstances, the direct S‐wave particle motion shows a flat plane, and that is perpendicular to the direct P‐wave motion direction. We combine these two properties to detect the S‐wave arrival of low‐SNR events. Our previous study applied spectral matrix (SPM) analysis to characterize the 3D particle motion of P waves. However, SPM analysis had limitations in detecting S‐wave arrivals. We then introduce the time‐delay components of the SPM (complex spectral matrix [cSPM]) to characterize the S‐wave particle motion, separate the S‐wave from the noise, and detect S‐wave arrivals. Using the cSPM analysis method, we assess the planarity and perpendicularity of the S‐wave polarization in the time and frequency domains. We then define a characteristic function that detects S‐wave arrivals by combining two properties, planarity and perpendicularity, to detect more low‐SNR events. The P–S travel time is obtained by setting the threshold values for the P‐ and S‐wave characteristic functions. We apply our method to 4 hr and 2 months of field data recorded at the Groningen field in the Netherlands. Our method successfully detects the P–S travel time of all catalog events and several additional undetected events. We locate the hypocenter of all events using the detected P–S travel times with a grid‐based search method."
Cover image: Detail of an earthquake map of the Groningen Gas Field in the Netherlands, (c) NLOG.NL (licensed for reuse with attribution) via Wikimedia Commons.