Auto-pick first breaks with complex raypaths for undulate surface conditions

An, Senyou; Hu, Tianyue; Cui, Yongfu; Wensheng, Duan; Peng, Gang

doi:10.1007/s11770-015-0468-2

Cited by 14 publications

(3 citation statements)

References 10 publications

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“…Wavelet-based threshold technology has been used to improve the SNR of the first-arrival signals by Gaci (2014). An et al (2015) also proposed an improved super-virtual interferometry (SVI) method to increase the stability of auto-picking first arrivals. The application of these methods has improved the accuracy of first-arrival picking, but in many cases, some wrong first arrivals are still unavoidable.…”

Section: Introductionmentioning

confidence: 99%

First-arrival automatic picking based on improved energy ratio method and outlier detection theory

Qin

Pan

et al. 2021

Acta Geophys.

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Based on the energy ratio method, an automatic picking method with strong noise resistance is proposed. It considers the influence of the current point's position on the first-arrival characteristic value. Specifically, an outlier detection technique is proposed to eliminate abnormal first arrivals for low signal-to-noise ratio (SNR) seismic data. First, the first arrivals of adjacent shots obtained by the new method are arranged according to the offsets. Then, combined with the distribution characteristics of the first arrivals, a symmetric window centered on the current point is established as the calculation range, and the distance-based outlier detection method is adopted for the abnormal first arrivals. The size of the calculation time window is determined by scanning the given value range. In order to optimize the processing results, we further propose an outlier detection method based on grid density. After this step, the abnormal first arrivals will be further eliminated. Following these steps, the abnormal first arrivals of all shots can be removed effectively. The actual data processing results show that the proposed program can accurately pick up the first arrivals and has a good performance in detecting the abnormal first arrivals. KeywordsFirst-arrival automatic picking • Abnormal first arrivals elimination • Distance-based outlier detection • Griddensity-based outlier detection Communicated by Prof. Sanyi Yuan (ASSOCIATE EDITOR), Prof. Michał Malinowski (CO-EDITOR-IN-CHIEF).

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Section: Introductionmentioning

confidence: 99%

First-arrival automatic picking based on improved energy ratio method and outlier detection theory

Qin

Pan

et al. 2021

Acta Geophys.

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“…Despite the success of SVI in improving the SNR of far-offset first-arrivals for both marine and land data (Hanafy et al, 2011;Bharadwaj et al, 2013;Vaezi and Meersman, 2014;Li et al, 2018) and its application to improve first break auto-picking (Al-Shuhail, 2015;An et al, 2015b) and residual statics estimation (Gao and Zhang, 2017), SVI applications have been until now mostly restricted to data recorded by 2D surveys. When SVI is applied to data recorded by 3D surveys, the source locations at x are not necessarily at the stationary positions (see Figure 2), which means that the correlated traces associated with different sources no longer share the same traveltimes and phases with one another, and summation of these correlated traces is insufficient to create a SNR-enhanced virtual trace with accurate phase information.…”

Section: Introductionmentioning

confidence: 99%

3D supervirtual refraction interferometry

Lü

Chávez‐Pérez

2020

GEOPHYSICS

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We have developed the theory and practice of 3D supervirtual interferometry (SVI) for enhancing the signal-to-noise ratio (S/N) of refraction arrivals in 3D data. Unlike 2D SVI, 3D SVI requires an extra integration along the inline direction to compute the stationary source-receiver pairs for enhanced stacking of the refraction events. The result is a significant increase in the S/N of first arrivals in the far-offset traces. We have evaluated 3D synthetic and field data examples to demonstrate the effectiveness of the proposed method. For the synthetic data tests, SVI has extended the source-receiver offset range of pickable traces from 11 to 15 km. In the field data example, SVI has extended the source-receiver offset of traces with pickable first-arrival traveltimes from 12 km to a maximum of 18 km, and the total number of reliable traveltime picks has increased by 12%, which contributes to a deeper velocity update in the traveltime tomogram.

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“…In the 1980s, Wu and Aki (1985) systematically investigated seismic wave scattering, including coda waves. Coda waves are multiply scattered during long-distance propagation and are sensitive to weak changes in the propagation medium (Kanu et al, 2014;An et al, 2015). Coda wave interferometry uses the differences before and after small disturbances to detect weak changes in propagation media.…”

Section: Introductionmentioning

confidence: 99%

Reservoir time-lapse variations and coda wave interferometry

Tang

Yao

et al. 2015

Appl. Geophys.

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Coda waves are multiply scattered waves that arrive much later than the major waves.Small seismic velocity variations are observed in reservoirs because of small variations in reservoir properties, which affect the fi rst arrivals. Hence, fi rst arrivals cannot be used to detect small seismic velocity variations. However, small variations can be reliably detected by the coda waves because of the amplification owing to multiple scattering. We investigate the ability of coda wave interferometry to detect seismic velocity variations and monitor time-lapse reservoir characteristics using numerical simulations and experimental data. We use the Marmousi II model and finite-difference methods to build model seismic data and introduce small seismic velocity variations in the target layer. We examine the model seismic data before and after the changes and observe the coda waves. We fi nd that velocity changes can be detected by coda wave interferometry and demonstrate that coda wave interferometry can be used in monitoring timelapse reservoir characteristics.

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Auto-pick first breaks with complex raypaths for undulate surface conditions

Cited by 14 publications

References 10 publications

First-arrival automatic picking based on improved energy ratio method and outlier detection theory

First-arrival automatic picking based on improved energy ratio method and outlier detection theory

3D supervirtual refraction interferometry

Reservoir time-lapse variations and coda wave interferometry

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