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Inverse Theory, Artificial Neural Networks

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Encyclopedia of Solid Earth Geophysics

Part of the book series: Encyclopedia of Earth Sciences Series ((EESS))

Introduction

Neural networks have been recognized for many years as a powerful tool for solving complex problems associated with pattern recognition, classification, and generalization, and have been used in geophysics in a large variety of different applications. The power of neural networks arises from their ability to emulate complex input/output mappings efficiently.

Comprehensive reviews may be found of all the major geophysical applications of neural networks in a number of excellent tutorial papers (Sandham and Leggett, 1998; Van der Baan and Jutten, 2000; Poulton, 2002). A number of books on the subject have also been published in the last decade (Poulton, 2001; Nikravesh et al., 2003; Sandham and Leggett, 2003).

In this present article, the fundamentals of geophysical inversion using neural networks are reviewed. In section “Geophysical inversion,” the physics of geophysical inversion are described, together with a short mathematical formulation. In section “Artificial neural...

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Authors and Affiliations

  1. Scotsig, 40 Westbourne Gardens, Glasgow, G12 9PF, UK

    William A. Sandham

  2. Ateeda Limited, 24 Canning Street, Edinburgh, EH3 8EG, UK

    David J. Hamilton

Authors
  1. William A. Sandham
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  2. David J. Hamilton
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Correspondence to William A. Sandham .

Editor information

Editors and Affiliations

  1. National Geophysical Research Institute, Council of Scientific and Industrial Research, Hyderabad, India

    Harsh K. Gupta

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Sandham, W.A., Hamilton, D.J. (2011). Inverse Theory, Artificial Neural Networks. In: Gupta, H.K. (eds) Encyclopedia of Solid Earth Geophysics. Encyclopedia of Earth Sciences Series. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-8702-7_35

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