Quantitative resource assessment methods play an increasing role in exploration for petroleum, water and minerals. This volume presents an international review on the state-of-the-art of the computerized methodology in resource exploration. The papers taken from those presented at the symposium are classified to either techniques, i.e., trend analysis; classification techniques; geostatistics; image analysis; expert systems/artificial intelligence; inventories; tomography and others, or to resources, i.e., petroleum, water, metals and non-metals.
Section headings and selected papers: Data Integration in Mineral
Exploration by Statistical and Multivariate Techniques. Statistical pattern
integration for mineral exploration, F P Agterberg et al . Intrinsic sample
methodology, D Harris & Guocheng ;an. Man-machine analysis of geological
maps, V V Marchenko & E A Nemir;vsky. Methods and techniques of the
prediction of metallic and nonmetallic raw materials using microcomputers in
Czechoslovakia, C Schejbal & J Hruska.; Data Integration in Mineral
Exploration by Image Processing and other Techniques. Use of image processing
and integrated analysis in exploration by Outokumpu Oy, Finland, J Aarnisalo.
Mappable data integration techniques in mineral exploration, D Bonnefoy & A L
Guill;n. The use of digital elevation models computed from SPOT stereopairs
for uranium exploration, P Leymarie et al . Applications in Petroleum
Exploration. Conditional simulation in oil exploration, H Burger et al .
Computer-assisted estimation of discovery and production of crude oil from
undiscovered accumulations, D J Forman & A L Hinde; Pore geometry evaluation
by petrographic image analysis, S M Habesch. Inventories. Geological
comparison of Brazil and China by state, J C Griffiths et al . Application of
Q-analysis to the GLOBAL databank: a geological comparison of the USSR and
the USA, D N Pilant et al . Explorational databases at the Geological Survey
of Finland, B Saltikoff & T Tarvain;n. Related Statistical Techniques.
Regression analysis of geochemical data with observations below detection
limit, Chang-Jo F Chung. Trend analysis on a personal computer: problems and
solutions, J E Robinson. Index.
Lisainfo e-raamatute kohta