利用环境地震噪声校正海底地震仪时钟

David Naranjo, Laura Parisi, Sigurjón Jónsson, Philippe Jousset, Dieter Werthmüller, C. Weemstra
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摘要

大洋底部地震仪(OBS)配备有地震传感器,可记录海底的声波和地震事件,因此适合用于调查能够在近海产生地震的构造结构。要获得准确的地震位置,一个关键参数是 OBS 所记录的传入地震信号的绝对时间。然而,由于全球导航卫星系统信号无法到达海底仪器,因此无法将 OBS 的内部时钟与已知参考时间同步。为了解决这个问题,我们在这里介绍一种新方法来同步大规模 OBS 部署的时钟。我们的方法依赖于环境地震噪声的延时(平均)交叉相关性的理论时间对称性。对称性的偏差归因于时钟误差。这意味着恢复的时钟误差将被非时钟误差引起的延时相互关系偏离对称性所掩盖。非均匀面波照明模式可以说是破坏时间对称性的最显著来源。我们利用实地数据证明,通过基于台站距离的加权最小二乘反演,可以减轻非均匀光照模式对恢复时钟误差的不利影响。此外,我们的方法还可以恢复 OBS 部署时的时间误差。这种误差可归因于:i) OBS 初始时间同步错误或 ii) OBS 沉入海底时温度和压力条件变化引起的时间误差。该方法在名为 OCloC 的开源 Python 软件包中实现,我们将其应用于冰岛雷克雅未克的 IMAGE 项目中获取的 OBS 记录。不出所料,大多数 OBS 都存在时钟漂移问题。令人惊讶的是,我们发现大多数 OBS 在部署时都出现了计时误差。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ocean Bottom Seismometer Clock Correction using Ambient Seismic Noise
Ocean-bottom seismometers (OBSs) are equipped with seismic sensors that record acoustic and seismic events at the seafloor, which makes them suitable for investigating tectonic structures capable of generating earthquakes offshore. One critical parameter to obtain accurate earthquake locations is the absolute time of the incoming seismic signals recorded by the OBSs. It is, however, not possible to synchronize the internal clocks of the OBSs with a known reference time, given that GNSS signals are unable to reach the instrument at the sea bottom. To address this issue, here we introduce a new method to synchronize the clocks of large-scale OBS deployments. Our approach relies on the theoretical time-symmetry of time-lapse (averaged) crosscorrelations of ambient seismic noise. Deviations from symmetry are attributed to clock errors. This implies that the recovered clock errors will be obscured by lapse crosscorrelations' deviations from symmetry that are not due to clock errors. Non-uniform surface wave illumination patterns are arguably the most notable source which breaks the time symmetry. Using field data, we demonstrate that the adverse effects of non-uniform illumination patterns on the recovered clock errors can be mitigated by means of a weighted least-squares inversion that is based on station-station distances. In addition, our methodology permits the recovery of timing errors at the time of deployment of the OBSs. This error can be attributed to either: i) a wrong initial time synchronization of the OBS or ii) a timing error induced by changing temperature and pressure conditions while the OBS is sunk to the ocean floor. The methodology is implemented in an open-source Python package named OCloC, and we applied it to the OBS recordings acquired in the context of the IMAGE project in and around Reykjanes, Iceland. As expected, most OBSs suffered from clock drift. Surprisingly, we found incurred timing errors at the time of deployment for most of the OBSs.
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