Correction to ‘Near Offset Reconstruction for Marine Seismic Data Using a Convolutional Neural Network’

IF 1.7 3区 地球科学 Q3 GEOCHEMISTRY & GEOPHYSICS
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引用次数: 0

Abstract

Huff, O.R., Thorkildsen, V.S., Greiner, T.L., Lie, J.E., Evensen, A.K., Bugge, A.J. et al. (2024) Near offset reconstruction for marine seismic data using a convolutional neural network. Geophysical Prospecting, 72, 2164–2185. https://doi.org/10.1111/1365-2478.13505

In Figure 12, the scaling factor applied to the CNN-predicted zero-offset section in Figure 12c and its spectrum in Figure 12f was incorrectly reported as 1.2 instead of 1.3. Accordingly, in Figure 12c, the label ‘1.2× amplitude’ should read: ‘1.3× amplitude’, and in Figure 12f, the label ‘CNN prediction (1.2×)’ should read: ‘CNN prediction (1.3×)’. In the caption of Figure 12, the text ‘(note that the amplitude is scaled by 1.2)’ and ‘The CNN prediction is scaled by 1.2’ should read: ‘(note that the amplitude is scaled by 1.3)’ and ‘The CNN prediction is scaled by 1.3’, respectively. The corrected Figure 12 and caption are provided below.

In addition, the corresponding text in the ‘Field Data Results’ section should be corrected as follows:

In the ‘Source-over-cable acquisition data (Barents Sea)’ subsection, the text ‘we scale the output of the CNN prediction by 1.2’ in paragraph 3 should read: ‘we scale the output of the CNN prediction by 1.3’, and the text ‘(previously scaled by 1.2 as explained in Figure 12)’ in paragraph 6 should read: ‘(previously scaled by 1.3 as explained in Figure 12)’.

In the ‘Conventional data (northern North Sea)’ subsection, the text ‘The CNN-predicted near offsets are not scaled by 1.2’ in paragraph 3 should read: ‘The CNN-predicted near offsets are not scaled by 1.3’, and the text ‘note the 1.2 scaling that was necessary to best match the spectra’ in paragraph 4 should read: ‘note the 1.3 scaling that was necessary to best match the spectra’.

We apologize for these errors.

卷积神经网络对海洋地震数据近偏移重建的修正
Huff, o.r., Thorkildsen, v.s., Greiner, t.l., Lie, j.e., Evensen, a.k., Bugge, A.J.等。(2024)基于卷积神经网络的海洋地震数据近偏移重建。地球物理勘探,32(2):664 - 6185。https://doi.org/10.1111/1365-2478.13505In图12,应用于图12c中cnn预测的零偏移部分及其图12f中的频谱的比例因子被错误地报告为1.2而不是1.3。因此,在图12c中,标签“1.2×幅度”应为“1.3×幅度”,在图12f中,标签“CNN预测(1.2×)”应为“CNN预测(1.3×)”。在图12的标题中,文本“(注意,幅度被缩放了1.2)”和“CNN预测被缩放了1.2”应该分别读作“(注意,幅度被缩放了1.3)”和“CNN预测被缩放了1.3”。更正后的图12和说明如下。此外,“现场数据结果”部分对应的文本应该更正如下:在“电缆上的源采集数据(巴伦支海)”小节中,第3段中的文本“我们将CNN预测的输出按1.2缩放”应该读为:“我们将CNN预测的输出按1.3缩放”,第6段中的文本“(之前按1.2缩放,如图12所示)”应该读为:“(之前按1.3缩放,如图12所示)”。在“常规数据(北海北部)”小节中,第3段的文本“cnn预测的近偏移量未按1.2缩放”应阅读为“cnn预测的近偏移量未按1.3缩放”,第4段的文本“注意1.2缩放是最佳匹配光谱所必需的”应阅读为“注意1.3缩放是最佳匹配光谱所必需的”。我们为这些错误道歉。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Geophysical Prospecting
Geophysical Prospecting 地学-地球化学与地球物理
CiteScore
4.90
自引率
11.50%
发文量
118
审稿时长
4.5 months
期刊介绍: Geophysical Prospecting publishes the best in primary research on the science of geophysics as it applies to the exploration, evaluation and extraction of earth resources. Drawing heavily on contributions from researchers in the oil and mineral exploration industries, the journal has a very practical slant. Although the journal provides a valuable forum for communication among workers in these fields, it is also ideally suited to researchers in academic geophysics.
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