Using Data‐Regrouping Methods to Attenuate Shot‐to‐Shot Coherent Interference Noise in Marine Seismic Data

Shen, Huijuan; Elboth, Thomas; Tao, Chunhui; Tian, Gang; Wang, Hanchuang; Qiu, Lei; Zhou, Jianping

doi:10.1029/2018ea000485

Cited by 2 publications

(1 citation statement)

References 18 publications

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“…The industry standard is using a multi‐shot approach to break the coherency of the data (Shen et al . ), thus giving the industry denoising an advantage over the neural network in denoising accuracy. This could in principle be done for the network as well, but will not be optimal since we want to keep the advantages of the network when it comes to fast‐track processing of large data volumes as well as in real‐time processing and quality control onboard seismic vessels during acquisition.…”

Section: Comparison Between the Customized U‐net And An Industry‐stanmentioning

confidence: 99%

Attenuation of marine seismic interference noise employing a customized U‐Net

Sun

Slang

Elboth

et al. 2020

Geophysical Prospecting

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A B S T R A C TMarine seismic interference noise occurs when energy from nearby marine seismic source vessels is recorded during a seismic survey. Such noise tends to be well preserved over large distances and causes coherent artefacts in the recorded data. Over the years, the industry has developed various denoising techniques for seismic interference removal, but although well performing, they are still time-consuming in use. Machine-learning-based processing represents an alternative approach, which may significantly improve the computational efficiency. In the case of conventional images, autoencoders are frequently employed for denoising purposes. However, due to the special characteristics of seismic data as well as the noise, autoencoders failed in the case of marine seismic interference noise. We, therefore, propose the use of a customized U-Net design with element-wise summation as part of the skip-connection blocks to handle the vanishing gradient problem and to ensure information fusion between high-and low-level features. To secure a realistic study, only seismic field data were employed, including 25,000 training examples. The customized U-Net was found to perform well, leaving only minor residuals, except for the case when seismic interference noise comes from the side. We further demonstrate that such noise can be treated by slightly increasing the depth of our network. Although our customized U-Net does not outperform a standard commercial algorithm in quality, it can (after proper training) read and process one single shot gather in approximately 0.02 s. This is significantly faster than any existing industry denoising algorithm. In addition, the proposed network processes shot gathers in a sequential order, which is an advantage compared with industry algorithms that typically require a multi-shot input to break the coherency of the noise.

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Section: Comparison Between the Customized U‐net And An Industry‐stanmentioning

confidence: 99%

Attenuation of marine seismic interference noise employing a customized U‐Net

Sun

Slang

Elboth

et al. 2020

Geophysical Prospecting

Self Cite

View full text Add to dashboard Cite

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Noise types and their attenuation in towed marine seismic: A tutorial

Hlebnikov

Elboth²,

Vinje³

et al. 2021

GEOPHYSICS

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The presence of noise in towed marine seismic data is a long-standing problem. The various types of noise present in marine seismic records are never truly random. Instead, seismic noise is more complex and often challenging to attenuate in seismic data processing. Therefore, we examine a wide range of real data examples contaminated by different types of noise including swell noise, seismic interference noise, strumming noise, passing vessel noise, vertical particle velocity noise, streamer hit and fishing gear noise, snapping shrimp noise, spike-like noise, cross-feed noise and streamer mounted devices noise. The noise examples investigated focus only on data acquired with analogue group-forming. Each noise type is classified based on its origin, coherency and frequency content. We then demonstrate how the noise component can be effectively attenuated through industry standard seismic processing techniques. In this tutorial, we avoid presenting the finest details of either the physics of the different types of noise themselves or the noise attenuation algorithms applied. Rather, we focus on presenting the noise problems themselves and show how well the community is able to address such noise. Our aim is that based on the provided insights, the geophysical community will be able to gain an appreciation of some of the most common types of noise encountered in marine towed seismic, in the hope to inspire more researchers to focus their attention on noise problems with greater potential industry impact.

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Using Data‐Regrouping Methods to Attenuate Shot‐to‐Shot Coherent Interference Noise in Marine Seismic Data

Cited by 2 publications

References 18 publications

Attenuation of marine seismic interference noise employing a customized U‐Net

Attenuation of marine seismic interference noise employing a customized U‐Net

Noise types and their attenuation in towed marine seismic: A tutorial

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