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.
