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  1. 2022
  2. 2D seismic
  3. Anisotropy
  4. Depth imaging
  5. Machine learning
  6. Publications

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Structural Geology is a Key to Seismic-Imaging Success

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Vestrum, R.W. and MacArthur, T.R., 2023, Structural Geology is a Key to Seismic-Imaging Success, AAPG Explorer.

  • Seismic data in structured land areas are characterised by low data density, low signal-to-noise ratios, and high structural complexity
  • Automated methods for velocity model building break down under these conditions
  • Structural-geology constraints are key to seismic imaging success in these areas, as illustrated graphically with this fault-geometry scenario test

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Written by

More entries in

  1. 2022
  2. 2D seismic
  3. Anisotropy
  4. Depth imaging
  5. Machine learning
  6. Publications

Download the publication

APGCE 2022: Convolutional neural networks to augment PSDM velocity model building

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Cameron, G.H. and Vestrum, R.W., 2022, Convolutional neural networks to augment PSDM velocity model building, APGCE Conference, Kuala Lumpur, Malaysia

  • Built convolutional neural network (CNN) to estimate TTI PSDM velocity models from shot gathers
  • Traditional automated methods for PSDM velocity estimation in complex-structure land areas are unstable, so we rely on the human understanding of the geology to build geologic models
  • The goal is to use machine learning to supplement human learning
  • Field-data example shows imaging improvements on certain shallow reflectors, which shows the potential of the method

Poster presentation

Greg presents poster in Kuala Lumpur

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