Structural imaging and event location require an accurate estimation of the seismic velocity.However, active seismic surveys used to estimate it are expensive and time-consuming. During the last decade, fiber-optic-based distributed acoustic sensing has emerged as a reliable, enduring, and high-resolution seismic sensing technology. We show how downhole distributed acoustic sensing passive records from the San Andreas Fault Observatory at Depth can be used for seismic velocity estimation. Using data recorded from earthquakes propagating near-vertically, we compute seismic velocities using first-break picking as well as slant stack decomposition. This methodology allows for the estimation of both P and S wave velocity models. We also use records of the ambient seismic field for interferometry and P wave velocity model extraction. Results are compared to a regional model obtained from surface seismic as well as a conventional downhole geophone survey. We find that using recorded earthquakes, we obtain the highest P wave model resolution. In addition, it is the only method that allows for S wave velocity estimation. Computed P and S models unravel three distinct areas at the depth range of 50-750 m, which were not present in the regional model. In addition, we find high V P /V S values near the surface and a possible V P /V S anomaly about 500 m deep. We confirm its existence by observing a strong S-P mode conversion at that depth.

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Seismograph self-noise has become a de facto standard for instrument comparisons and their performance assessment and is considered as one of the most vital parameters for instrument comparison. For self-noise testing of modern force-balance feedback broadband seismometers, several factors have been thoroughly discussed and thought to be attributable to the self-noise estimate, including the data selection criteria, sensor alignment correction, timing error, correlation analysis method, and computational parameter selection during the computational process. This study focuses on some other factors, such as local site conditions, temperature insulating methods, and data logger self-noise interferences, with an aim to differentiate the self-noise contribution of these sources and their dependencies on time and frequency. A series of experiments were conducted at the Beijing National Earth Observatory using a Trillium 120QA seismometer and Reftek-130 data acquisition system at three different locations ranging from the ordinary equipment warehouse to global seismographic network level cave with a hardrock base. Results show that noise-free site is necessary for the self-noise test in a frequency band greater than approximately 0.1 Hz. However, for a frequency band less than 0.1 Hz, the insulation method and installation procedures are far more important, although the influence of the site location cannot be neglected fully. A suitable preamp should be selected in the data logger configurations to ensure that the low-noise amplitude of the sensor signal is above the digitizer noise level.

The horizontal orientation estimation of an ocean-bottom seismometer (OBS) is critical for providing reliable data for seismological studies. In this article, we applied three independent polarization analysis methods to estimate the absolute horizontal orientation of a pilot shallow-water OBS array in Bohai Sea, China. The OBS array was deployed in the autumn of 2018 and comprised 32 broadband seismometers lasting around 1 yr, aimed at investigating the geodynamics of North China craton and adjacent areas. The timings of the data were corrected through the correlation analysis of regional and teleseismic earthquake events, before the polarization analysis. Polarization analysis using P wave and Rayleigh wave, from both natural earthquakes and noise cross correlations, was performed. In total, 28 out of 29 stations obtained the effective estimates combining the three methods, of which 11 stations showed relatively robust results with variations well below 10° among the three methods. However, the superiority of one method over the others is not obvious. As there is a trade-off between the accepted final estimates and the number of qualified measurements defined by parameters such as the correlation coefficient threshold, window length, and filtering options, we investigated these effects using 15 different groups of parameters for the three methods, and the deviation statistics showed a distribution with the root mean square deviation of 9.2° for the whole array.