Geophysical Applications of Artificial Neural Networks and Fuzzy Logic

  • William A. Sandham
  • Miles Leggett

Part of the Modern Approaches in Geophysics book series (MAGE, volume 21)

Table of contents

  1. Front Matter
    Pages i-xxi
  2. Exploration Seismology

  3. Lithology, Well Logs, Prospectivity Mapping and Reservoir Characterisation

  4. Electromagnetic Exploration

    1. Front Matter
      Pages 251-251
    2. Edmund Winkler, Wolfgang Seiberl, Andreas Ahl
      Pages 253-265
  5. Other Geophysical Applications

  6. Back Matter
    Pages 305-325

About this book


The past fifteen years has witnessed an explosive growth in the fundamental research and applications of artificial neural networks (ANNs) and fuzzy logic (FL). The main impetus behind this growth has been the ability of such methods to offer solutions not amenable to conventional techniques, particularly in application domains involving pattern recognition, prediction and control. Although the origins of ANNs and FL may be traced back to the 1940s and 1960s, respectively, the most rapid progress has only been achieved in the last fifteen years. This has been due to significant theoretical advances in our understanding of ANNs and FL, complemented by major technological developments in high-speed computing. In geophysics, ANNs and FL have enjoyed significant success and are now employed routinely in the following areas (amongst others): 1. Exploration Seismology. (a) Seismic data processing (trace editing; first break picking; deconvolution and multiple suppression; wavelet estimation; velocity analysis; noise identification/reduction; statics analysis; dataset matching/prediction, attenuation), (b) AVO analysis, (c) Chimneys, (d) Compression I dimensionality reduction, (e) Shear-wave analysis, (f) Interpretation (event tracking; lithology prediction and well-log analysis; prospect appraisal; hydrocarbon prediction; inversion; reservoir characterisation; quality assessment; tomography). 2. Earthquake Seismology and Subterranean Nuclear Explosions. 3. Mineral Exploration. 4. Electromagnetic I Potential Field Exploration. (a) Electromagnetic methods, (b) Potential field methods, (c) Ground penetrating radar, (d) Remote sensing, (e) inversion.


Fuzzy Information Map Reservoir artificial intelligence classification fuzzy logic geophysics intelligence

Editors and affiliations

  • William A. Sandham
    • 1
  • Miles Leggett
    • 2
  1. 1.University of StrathclydeGlasgowScotland, UK
  2. 2.Jason Geosystems bvRotterdamThe Netherlands

Bibliographic information

  • DOI
  • Copyright Information Springer Science+Business Media B.V. 2003
  • Publisher Name Springer, Dordrecht
  • eBook Packages Springer Book Archive
  • Print ISBN 978-90-481-6476-9
  • Online ISBN 978-94-017-0271-3
  • Series Print ISSN 0924-6096
  • Buy this book on publisher's site