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ZENODO
Dataset . 2021
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ZENODO
Dataset . 2021
License: CC BY
Data sources: ZENODO
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ZENODO
Dataset . 2021
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2021
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2021
License: CC BY
Data sources: ZENODO
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Smithsonian figshare
Dataset . 2021
License: CC BY
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Deep learning for simultaneously interpreting 3D seismic horizons and faults by estimating a relative geologic time volume

Authors: Bi Zhengfa (10349388); Wu Xinming (10349391); Geng Zhicheng (10349394); Li Haishan (10349397);

Deep learning for simultaneously interpreting 3D seismic horizons and faults by estimating a relative geologic time volume

Abstract

To train our deep convolutional neural network for Relative Geologic Time (RGT) estimation and fault detection tasks, we automatically generate 400 pairs of synthetic training datasets including 3D seismic images and the corresponding label images (including RGT and fault volumes) with the ground truth of the geologic structures simulated in the seismic images. 1) The "seis.zip" contains 400 3D seismic images and each image is with the dimension of 128X256X256; 2) The "rgt.zip" contains 400 RGT volumes and each volume is with the same dimension of 128X256X256. 3) The "fault.zip" contains 400 label images of the faults and each label image is with the same dimension of 128X256X256.

Keywords

Science Policy, label, 128 X 256X, 3 D, 400 RGT volumes, 400 3 D, Relative Geologic Time, Space Science, dimension, fault detection tasks, quot, image, Biological Sciences not elsewhere classified

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
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