| Geophysical Applications of Artificial Neural Networks and Fuzzy Logic [With CDROM] 2003 Edition Contributor(s): Sandham, W. (Editor), Aminzadeh, Fred (Preface by), Leggett, M. (Editor) |
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ISBN: 1402017294 ISBN-13: 9781402017292 Publisher: Springer OUR PRICE: $104.49 Product Type: Hardcover - Other Formats Published: December 2003 Annotation: This book is the first major text to encompass the wide diversity of geophysical applications of artificial neural networks (ANNs) and fuzzy logic (FZ). Each chapter, written by internationally-renowned experts in their field, represents a specific geophysical application, ranging from first-break picking and trace editing encountered in seismic exploration, through well-log lithology determination, to electromagnetic exploration and earthquake seismology. The book offers a well-balanced division of contributions from industry and academia, and includes a comprehensive, up-to-date bibliography covering all major publications in geophysical applications of ANNs and FZ. A special feature of this volume is the preface written by Professor Fred Aminzadeh, eminent authority in the field of artificial intelligence and geophysics. The enclosed CD-ROM contains full colour figures and searchable files, as well as short biographies of the editors. |
| Additional Information |
| BISAC Categories: - Science | Physics - Geophysics - Computers | Neural Networks - Computers | Intelligence (ai) & Semantics |
| Dewey: 622.159 |
| LCCN: 2003065329 |
| Series: Modern Approaches in Geophysics |
| Physical Information: 0.44" H x 6.18" W x 9.88" (1.68 lbs) 325 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: 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. |