Computer Applications in Resource Estimation

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 Pan. Man-machine analysis of geological maps, V V Marchenko & E A Nemirovsky. 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 Guillen. 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 Tarvainen. 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.