Download Advanced Geostatistics in the Mining Industry: Proceedings by G. Matheron (auth.), Massimo Guarascio, Michel David, PDF

By G. Matheron (auth.), Massimo Guarascio, Michel David, Charles Huijbregts (eds.)

When Prof. Hatheron used to be requested to delineate the background of geostatistics, he objected that such self-discipline continues to be too "young" to be handled from a historic perspective. The an increasing number of expanding sensible functions requiring more moderen and more moderen methodologies may really recommend the need of empha­ sizing the stairs taken and the consequences got in past times. the explanation of definite epistemological offerings in addition to the difficul­ ties and good fortune in constructing a discussion with the folk probably to learn from the result of geostatistics are priceless premises to appreciate the current prestige of this self-discipline. The human bearing of characters of the folks that experience introduc­ ed and studied this technological know-how mixing conception with monetary prac­ tics is an element enjoying a no longer inconsiderable function within the improve­ ment of geostatistics. those suggestions have been the ideas in organizing the ASI-Geo­ stat seventy five. Canada, France and Italy are 3 varied events in an business and educational context, in particular within the interac­ tion among those fields. but it was once our influence that the time had come to gather specialists, students, and people in­ terested in geostatistics with a view to overview its current posi­ tion on a number of degrees within the diversified international locations and to debate its destiny clients. Prof. Hatheron and Hr. Krige in addition to different in demand humans have been of an identical opinion.

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Extra info for Advanced Geostatistics in the Mining Industry: Proceedings of the NATO Advanced Study Institute held at the Istituto di Geologia Applicata of the University of Rome, Italy, 13–25 October 1975

Example text

C'est Ie type Ie plus frequemment utilise en geostatistique miniere. A titre de prerequisite, il faut connaitre Ie variogramme y (x;y) ,. 2'I E(Z(x) - Z(y» 2 Pour que l'inference statistique soit possible (condition all on peut adopter Ie modele des FA! d'ordre 0 : car alors y(x;y) ~ y(x- y) et I 'inference est raisonnablement possible au moins pour les premiers points de y(h) (seuls necessaires pour effectuer un 24 G. MATHERON krigeage sur un v0181nage l imi te du panneau A estimer). Mais la condition cl n'est pas toujours verifiee .

Note tha t this solution offers the po: sibility of cheaply computing the estimation variance. A good example of random kriging in 3-D is given by Huijbreg" in David (1974). It concerns a porphyry molybdenum deposit which is "ra ndomlyll proven by drill holes . The blocks which are estima· ted are 100' x 100' X 30' and their grade is obtained as a weighted average of the i nformation inside the block V, itself (n. , averaging t 1. unerous in rich areas). This means one sets bounds on the minimum information required to estimate a block.

Its cOSt will probably be acceptable. We can quote several mines wile] it generates block estimates for I e , 2e each. The experienced geostatistician will try in addition to take advantage of some pm ticular situations and save even more, mostly by avoiding the com· putation of covariances. These are the punctual kriging, random kriging, and fixed sampling deSign techniques which we previously announced. They are especially useful for debugging a kriging problem, like testing the effect of the variation of such and sud parameter.

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