Computer Applications in Resource Estimation. Prediction and by Gabor Gaal, G. Gaal, D. F. Merriam

By Gabor Gaal, G. Gaal, D. F. Merriam

Quantitative source evaluate tools play an expanding function in exploration for petroleum, water and minerals. This quantity provides a global overview at the cutting-edge of the automatic technique in source exploration. The papers taken from these awarded on the symposium are labeled to both strategies, i.e., development research; category options; geostatistics; picture research; specialist systems/artificial intelligence; inventories; tomography and others, or to assets, i.e., petroleum, water, metals and non-metals

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The compositing reduced the s a m p l i n g error and increased t h e statistical stability of t h e t r a i n i n g data. T h e composite s a m p l e s of the Nordkalott project were grouped a n d t h e grouped s a m p l e s were analyzed to achieve t h e s a m e s a m p l i n g density and t h e s a m e analytical procedure for both s e t s of data. ICAP a n a l y s e s were done for both partial leach (aqua regia) a n d total dissolution (hydrofluorine a n d boric acids). The e l e m e n t s included in t h e classification w e r e for t h e partial leach Ba, Ca, Cr, F e , Mg, Μη, N a , Ρ, Ti, V, a n d Y and for the total dissolution Co, Cu, Fe, La, Li, Mn, Ni, P, Sc, Th, Ti, V, Y, a n d Zn.

T h i s is restríctive, be­ cause the l e a s t significant factors associated with t h e l e a s t reliable variables are i n t e r e s t i n g for the interpretation of geological processes. DISCUSSION The m e t h o d is easy to u s e because m o d e l s are created by d e m a r c a t i n g the desired training a r e a s and the s a m p l i n g material of t h e m o d e l s is of t h e s a m e type a s the s a m p l i n g material to be classified. T h e material m u s t b e selected to reflect t h e characterístic features of t h e areas, however, otherwise the m o d e l s become too general a n d t h e r e s u l t a n t areas of favorability e x t e n d too widely.

Geology, V. 8 3 , no. l , p . 18-29. A. : Artificial intelligence and statistics: Addison-Wesley, Reading, M a s s a c h u s e t t s , p. 17-55. , 1 9 8 4 , Statistical and k n o w l e d g e - b a s e d approaches to chnical decision-support s y s t e m s , with a n application in gastroen­ terology: Jour. Royal Statist. Soc. A, v. 1 4 7 , pt. 1, p. 35-77. , 1 9 8 8 , Spatial data integration of l a k e - s e d i m e n t geochemistry, geology a n d gold occurrences, M e g u m a Terrane, eastern N o v a Scotia: Proc.

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