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- W2037315823 abstract "A neural network uses a supervised learning algorithm to perform multiple prediction and attenuation. The network recognizes that information about mupltiple energy content of the seismic data is present in various data domains and data attributes. It extracts the information from training examples and is able to predict and attenuate multiple energy. We show the performance of the novel algorithm when applied to synthetic acoustic and elastic prestack seismic data containing various types of multiples (internal and free surface). Thus the neural network is able to separate primary and multiple energy in a data-adaptive and automatic manner." @default.
- W2037315823 created "2016-06-24" @default.
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- W2037315823 date "2000-01-01" @default.
- W2037315823 modified "2023-10-06" @default.
- W2037315823 title "Multiple attenuation with attribute‐based neural networks" @default.
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- W2037315823 doi "https://doi.org/10.1190/1.1815827" @default.
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