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...
| Main Authors: | , , , , |
|---|---|
| Format: | Conference Paper |
| Published: |
2019
|
| Online Access: | http://hdl.handle.net/20.500.11937/76413 |