P–S Travel-Time Detection and Hypocenter Location of Low-SNR Events Using Polarization in the Time–Frequency Domain

震源 时域 极化(电化学) 物理 微震 平面度测试 平面波 横波 地震学 光学 声学 地质学 计算物理学 计算机科学 数学 化学 诱发地震 组合数学 物理化学 计算机视觉
作者
Jingyi Sun,Yusuke Mukuhira,Takayuki Nagata,Taku Nonomura,Michael C. Fehler,Hirokazu Moriya,Nori Nakata,Takatoshi Ito
出处
期刊:Bulletin of the Seismological Society of America [Seismological Society of America]
标识
DOI:10.1785/0120230280
摘要

ABSTRACT 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.
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