Saturday, 18 February 2023, 08:00-17:00 | Le Meridien Hotel, Bahrain

PRACTICAL MACHINE LEARNING METHODS IN THE GEOSCIENCES

ORGANISER

SEG

OVERVIEW

Learn the high-level principles of five important topics in machine learning: neural networks; convolutional neural networks; support vector machines; principal component analysis; clustering methods. Practical examples in geosciences will be used to show applications of each method. Practice the execution of these methods on MATLAB and Keras codes.

Teaching format is 50-minute lectures and 1-hour labs to reinforce principles of each method. A selective overview of important ML topics is provided, and their practical understanding comes from MATLAB exercises. Machine learning examples are taken from the fields of astronomy, medicine, geosciences, and material sciences.

WHO SHOULD ATTEND?

The short course is for physical scientists who have heard about ML and might know some details but lack enough knowledge to assess ML applications in their specialty.

COURSE OBJECTIVES

  • Learn how to apply ML methods to geoscience examples
  • Understand key principles underlying each of the ML methods
  • Practice manipulating MATLAB and Keras ML codes so they can adapt the codes to their own problems
  • Understand limitations and benefits of each ML method

INSTRUCTOR

Gerard Schuster

Gerard Schuster

Gerard Schuster is currently a Professor of Geophysics at King Abdullah University Science and Technology (KAUST) and an adjunct Professor of Geophysics at University of Utah. He was the founder and director of the Utah Tomography and Modeling/Migration consortium from 1987 to 2009, and is now the co-director and founder of the Center for Fluid Modeling and Seismic Imaging at KAUST. Dr. Schuster helped pioneer seismic interferometry and its practical applications in applied geophysics, through his active research program and through his extensive publications, including his book “Seismic Interferometry” (Cambridge Press, 2009). He also has extensive experience in developing innovative migration and inversion methods for both exploration and earthquake seismology.

Gerard has an MS (1982) and a PhD (1984) from Columbia University and was a postdoctoral researcher there from 1984-1985. From 1985 to 2009 he was a professor of Geophysics at University of Utah. He left Utah to start his current position as Professor of Geophysics at KAUST in 2009. He received a number of teaching and research awards while at University of Utah. He was editor of Geophysics from 2004-2005 and was awarded SEG’s Virgil Kauffman gold medal in 2010 for his work in seismic interferometry.

SEG published Gerard’s book Seismic Inversion in late 2017 and is considering publishing his almost completed book Practical Machine Learning Methods in The Geosciences.

REGISTRATION FEES

SEG MEMBERS US$ 685 + VAT
NON-SEG MEMBERS US$ 785 + VAT
STUDENTS US$ 200 + VAT

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