Session: ML in Seismic Interpretation

Date and time: 20 March, 15:55 – 17:35

Location: Main Stage

Use the links below to evaluate the talks:

1. Fully automatic procedure of fault surfaces detection presented by A. Kozhevin
Authors: A. Kozhevin, S. Tsimfer ()
2. Exploring the Potential of Denoising Diffusion Probabilistic Models for Generating Realistic Geological Rock Thin Section Images presented by R. Perez
Authors: R. Perez1 (1 University Of Vienna)
3. Machine learning application for joint rock-physics model optimization, facies classification and compaction modeling: North Sea Example presented by R. Filograsso
Authors: R. Filograsso1, A. Mur1, R. Beloborodov2, M. Pervukhina2 (1 Ikon Science; 2 CSIRO)
4. Prediction of Bedrock Depth in Complex Mining Areas using Machine Learning Algorithms presented by A. Najafabadipour
Authors: A. Najafabadipour1, S. Najafabadipour2 (1 Shahid Bahonar University of Kerman; 2 Allameh Tabataba’i University)
5. Rock property prediction ahead of the drilling bit using Dynamic Time Warping and Machine Learning regression presented by A. Christ
Authors: A. Christ1, A. Bouziat1, C. Cornet1, Y. Djemame2, J. Fortun2, J. Lecomte1, A. Meunier2, P.N.J. Rasolofosaon1 (1 IFP Energies nouvelles; 2 Perenco)

Speakers share their expertise and insight during the EAGE Digital 2023 programme. Would you help them by answering a few questions about their talks? Best evaluated talks can receive an increased exposure and recognition through the below:

  • be invited to submit a paper for one of EAGE’s journals
  • be invited to participate in the Distinguished Lecturer programme
  • be invited to record an a-lecture
  • be part of a ‘Best of’ exchange with another event or association
  • be invited to become EAGE’s instructor

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