Arrival-time picking method based on approximate negentropy for microseismic data

Li, Yue; Ni, Zhuo; Tian, Yanan

doi:10.1016/j.jappgeo.2018.03.012

Cited by 17 publications

(3 citation statements)

References 19 publications

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“…Negentropy definition is based on the entropy and it is also widely used to detect non-Gaussian features. Yue Li (2018) proposed an arrival-time picking method based on negentropy for microseismic data. In this study, the negentropy is applied to borehole strain at Guza station associated with the Wenchuan earthquake, approximated by skewness and kurtosis.…”

Section: Interactive Commentmentioning

confidence: 99%

Response to Reviewer 1

Yu¹

2019

Preprint

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Section: Interactive Commentmentioning

confidence: 99%

Response to Reviewer 1

Yu¹

2019

Preprint

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“…They improved this method using an edge-preserving smoothing (EPS) filter. Li et al (2018) selected an appropriate negentropy approximation to minimize the effect of the SNR according to the observed information characteristics and distinguished the regions of signals and noises to detect the first-arrival time.…”

Section: Introductionmentioning

confidence: 99%

“…Li et al. (2018) selected an appropriate negentropy approximation to minimize the effect of the SNR according to the observed information characteristics and distinguished the regions of signals and noises to detect the first‐arrival time. In recent years, image‐processing techniques have also been applied in first‐arrival picking.…”

Section: Introductionmentioning

confidence: 99%

A first‐arrival wave recognition method based on the optimal dominant energy spectrum

Liu

et al. 2022

Geophysical Prospecting

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Refraction seismic data acquired by wide‐angle ocean‐bottom seismometers are typically used to invert geological structures. Accurate and reliable first‐arrival traveltime picks are therefore critical to successful refraction data processing. Unfortunately, signal‐to‐noise ratios of refraction data acquired by wide‐angle ocean‐bottom seismometers at far offsets are usually low; thus, conventional methods such as the energy ratio method and correlation analysis method usually fail to accurately and efficiently determine the refraction phase. We therefore develop a novel first‐arrival wave recognition method based on the optimal dominant energy spectrum to improve the accuracy of refraction wave picking on wide‐angle ocean‐bottom seismometer data. The method consists of three steps. The first step is to obtain the optimal dominant energy spectrum according to the power spectrum density of sample scanning. Second, the initial position of the first‐arrival wave is recognized by combining the range of the optimal dominant energy spectrum and the maximum point of its derivative. Third, the modified cross‐correlation method adjusts the initial position to obtain a more accurate arrival time. In this paper, we illustrate the workflow and feasibility of the proposed method via testing on model data. Then, the method is used to determine the first‐arrival time of field wide‐angle ocean‐bottom seismometer data acquired in the Southwest Pacific Ocean and Xisha Islands. The results show that our method can accurately pick the refraction phase at offsets as far as 80 km, thus significantly reducing the uncertainties in first‐arrival phase picking.

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