Geophysical Signal Processing Using Neural Networks by Kou-Yuan Huang

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Summary

A comprehensive book on the role of neural networks in seismic signal processing problems, specifically in seismic pattern recognition, and well log data inversion, utilizing the theory of John J. Hopfield, who won the 2024 Nobel Prize in Physics.

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Geophysical Signal Processing Using Neural Networks by Kou-Yuan Huang

A comprehensive book for the geophysical exploration community on the role of neural networks in seismic signal processing problems, specifically in seismic pattern recognition, and well log data inversion. It uses the theory of John J. Hopfield, who won the 2024 Nobel Prize in Physics, to detect the seismic pattern, to solve the seismic horizon picking, and to determine the seismic velocity picking. Key topics include perceptron for classification of seismic Ricker wavelets and detection of seismic anomalies, neural network for seismic principal component analysis, Hough transform neural network for seismic pattern detection, simulated annealing for seismic pattern detection, cellular neural network for seismic pattern recognition, improved machine learning and deep learning, well log data inversion using multilayer perceptron (MLP), and expanded radial basis function network (RBF).

Features

  • Covers significant advancements in deep learning and neural networks used for seismic pattern recognition.
  • Presents Hopfield neural networks for seismic signal processing.
  • Explores well log data inversion using neural networks.
  • Discusses simulated annealing for pattern detection and seismic applications.
  • Explains the need for neural networks in the petroleum industry for oil and gas exploration.

This is an excellent book for graduate and postgraduate students, and professionals in the petroleum, oil, and gas industries, as well as those with an interest in geophysical exploration.

Kou-Yuan Huang is a Professor with the Department of Computer Science, National Yang Ming Chiao Tung University, Hsinchu, Taiwan. He received his Ph.D. degree in Electrical Engineering from Purdue University, IN, USA. He has authored five books on topics related to syntactic pattern recognition and neural networks and has published 24 journal papers, 10 book chapters, and 138 conference papers, mostly at top conferences such as International Joint Conference on Neural Networks (IJCNN), IEEE International Geoscience and Remote Sensing Symposium (IGARSS), and International Meeting of Society of Exploration Geophysicists (SEG). He is an IEEE Life Member and SEG member.

SKU Unavailable
ISBN 13 9781041081944
Title Geophysical Signal Processing Using Neural Networks
Author Kou-Yuan Huang
Series Signal And Image Processing Of Earth Observations
Condition Unavailable
Binding Type Hardback
Publisher Taylor & Francis Ltd
Number of pages 328
Cover note Book picture is for illustrative purposes only, actual binding, cover or edition may vary.