Short Course

SC-10: Fundamentals of Seismic Attributes and Attribute-Driven Machine Learning for Seismic Interpretation

Monday, 17 August | 8:00 a.m.–5:00 p.m. |

Sponsored by SEG

Geoscience students and professionals with some familiarity with how seismic attributes are used.

• Seismic attributes and multiattribute display (2h)
• Seismic data conditioning (1h)
• Unsupervised machine learning (2.5h)
• Supervised machine learning and explainable AI (2.5h)

• What attribute(s) should I use to map a given geologic objective?
• How can I improve the attribute and machine learning clustering/classification response of migrated data through data conditioning?
• What attributes should I use for multiattribute machine learning analysis?
• What are the differences between unsupervised, unsupervised using geological knowledge, and supervised machine learning techniques for seismic interpretation?
• How can machine learning results help us understand the attribute sensitivity to geologic objectives?

Course Leader(s)

  • 50
    David Lubo-Robles,
    University of Oklahoma
  • 50
    Kurt Marfurt,
    University of Oklahoma
  • 50
  • 50
  • 50
  • 50
  • 50

$500 Member
$650 Nonmember
$200 Student

25

1.5 CEUs
15 Professional Development Hours

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