Evaluating and correcting short-term clock drift in data from temporary seismic deployments

Abbas, Aqeel; Zhu, Gaohua; Zi, Jinping; Chen, Han; Yang, Hongfeng

doi:10.1016/j.eqrea.2022.100199

Cited by 4 publications

(2 citation statements)

References 66 publications

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“…However, the time length of cross-correlation must be shortened from one day to hours to increase the total number of correlated traces before selected stacking. Daily cross-correlation has no scientific justification except for the ease of data access (Abbas et al, 2022;Prieto et al, 2009;Seats et al, 2012). We also tested Welch's method (Welch, 1967) by overlapping the calculated waveform using the optimal parameters from Seats et al (2012) (Figure 3).…”

Section: Cross-correlationmentioning

confidence: 99%

Ambient Noise Interferometry Using Ocean Bottom Seismometer Data From Active Source Experiments Conducted in the Southernmost Mariana Trench

Zhang,

Xu,

Xiao

et al. 2024

JGR Solid Earth

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Ocean bottom seismometers (OBSs) have been used to detect submarine structural and tectonic information for decades. According to signal source controllability, OBS data have generally been classified into active and passive source data categories. The former mainly focuses on the compressional wave (P‐wave) velocity inversion and always lacks valid information about the shear wave (S‐wave) velocity structure. While the latter provides structural information with limited resolution due to the aperture of the stations. Overcoming the barriers between processing these two data types will allow the reuse of a vast amount of data from active source experiments to explore the submarine S‐wave velocity structural properties. Here, we creatively applied ambient noise interferometry to invert the S‐wave velocity structure using data from active source OBS deployment conducted in the southernmost Mariana subduction zone, which had already been utilized to detect submarine P‐wave velocity structure. Considering the short time duration and relatively low quality of this type of data, a combined method of short‐segment cross‐correlation and selected time‐frequency domain phase‐weighted stacking was adopted to obtain stable cross‐correlation functions, which were subsequently used to invert S‐wave velocity structures. Compared to previous studies using different methods, our result sheds new light on the crust and upper mantle structure of the southernmost Mariana subduction zone. This method could be used to detect more information based on the reutilization of existing active source OBS data.

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Section: Cross-correlationmentioning

confidence: 99%

Ambient Noise Interferometry Using Ocean Bottom Seismometer Data From Active Source Experiments Conducted in the Southernmost Mariana Trench

Zhang,

Xu,

Xiao

et al. 2024

JGR Solid Earth

Self Cite

View full text Add to dashboard Cite

show abstract

“…In addition, relying on long-term NCF can mask sudden changes in station clocks. Hable et al (2018) introduced multi-component superposition and Abbas et al (2022) aimed to improve accuracy and expand frequency range, but these are more suitable for fixed networks that can record longterm data. Due to the relatively simple deployment and short working time of temporary networks, the duration of NCF obtained from their observation data is shorter and more susceptible to the impact of instrument clock offset.…”

mentioning

confidence: 99%

Using high-precision travel time extraction to detect time deviation of seismic instruments

Zhang,

Ye,

Jin

et al. 2024

Meas. Sci. Technol.

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The method of seismic ambient noise cross-correlations (NCFs) has been demonstrated to be applicable for time offset measurement, especially in evaluating instrument clocks. Continuous recording of seismic ambient noise data makes it possible to analyze the performance of seismic instruments online. However, long-term cross-correlation and stacking calculations are required to obtain accurate travel time from ambient noise, which greatly reduces the time resolution of instrument performance detection. Therefore, we propose a travel time extraction method based on time–frequency analysis, which could obtain the travel time accurately even though the NCF has a low signal-to-noise ratio (SNR), and it is applied to the measurement of clock offsets in seismic instruments. The method combines S Transform and dictionary learning to improve the SNR of NCFs, and uses a peak extraction algorithm based on short-time Fourier transform to obtain accurate travel times. Additionally, the travel time drift of the station pair can be obtained by calculating the travel time difference between causal and acausal parts of NCFs. Using the data from ambient noise observations and the real data with time errors to verify that the proposed method can obtain accurate travel time for NCF with SNR lower than 6 and it can pick up a time offset as low as one sampling point, the detectable change is 0.046% of travel time, which is crucial for detecting weak changes in the performance of seismic instruments.

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The seismicity in the middle section of the Altyn Tagh Fault system revealed by a dense nodal seismic array

Yao,

Xu,

Sang

et al. 2024

Earthquake Research Advances

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Evaluating and correcting short-term clock drift in data from temporary seismic deployments

Cited by 4 publications

References 66 publications

Ambient Noise Interferometry Using Ocean Bottom Seismometer Data From Active Source Experiments Conducted in the Southernmost Mariana Trench

Ambient Noise Interferometry Using Ocean Bottom Seismometer Data From Active Source Experiments Conducted in the Southernmost Mariana Trench

Using high-precision travel time extraction to detect time deviation of seismic instruments

The seismicity in the middle section of the Altyn Tagh Fault system revealed by a dense nodal seismic array

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