Seismic Inversion with Deep Neural Networks: a Feasibility Analysis

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Seismic Inversion with Deep Neural Networks: a Feasibility Analysis

We investigate deep learning approaches to inversion of a 1D model of the subsurface using synthetic surface seismic and VSP data. Several deep neural networks based on three different architectures are developed and tested. The matrix propagator technique is used to generate the synthetic data for...

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Bibliographic Details
Main Authors:	Puzyrev, Vladimir, Egorov, Anton, Pirogova, Anastasia, Elders, Christopher, Otto, Claus
Format:	Conference Paper
Published:	2019
Online Access:	http://hdl.handle.net/20.500.11937/76413

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