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

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

When Prof. Hatheron used to be requested to delineate the historical past of geostatistics, he objected that such self-discipline continues to be too "young" to be handled from a old standpoint. The increasingly more expanding useful functions requiring more recent and more recent methodologies could relatively recommend the need of empha­ sizing the stairs taken and the implications bought during the past. the explanation of sure epistemological offerings in addition to the difficul­ ties and good fortune in developing a discussion with the folks probably to learn from the result of geostatistics are helpful 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 thought with monetary prac­ tics is an element enjoying a no longer inconsiderable position within the strengthen­ ment of geostatistics. those innovations have been the information in organizing the ASI-Geo­ stat seventy five. Canada, France and Italy are 3 various occasions in an commercial and educational context, particularly within the interac­ tion among those fields. but it used to be our influence that the time had come to gather specialists, students, and folks in­ terested in geostatistics so as to evaluation its current posi­ tion on a variety of degrees within the various nations and to debate its destiny clients. Prof. Hatheron and Hr. Krige in addition to different renowned humans have been of an analogous 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

Avec r J..! • I , l'e s timateur aff i n e r entre toujours, en realite , . dans la classe SUlvante ; - Les estimateurs 1ineaires autorises a l'ordre 0, du type , , z ", r , , A. , 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.

It is also true that i f a brute force method is appli ed, Simply following the standard kriging algorithm, the computing cost will be more than for other methods. Before we proceed, let us have a l ook at a few figures. I t should be remembered that to uS kriging is an engine ering tool, geared to solve real economic problems. Let us considerer for a moment a typical open pit, mining 10 Mt M. GUllrDSCio tt III. ). AdvDnced GeostariJrics in the M;ninglnduJ/ry. 31 48. All Righrs Rtterved. Copyright CI 1976 by D.

La plus puissante consiste a former 1 'esperance conditionnelle de la teneur du panneau lorsque celles des prelevements sont connues. Mais (sans parler des difficultes a peu pres inextricables aux- 23 LE CHOIX DES MODELES EN GEOSTATlSTlQUI:. quelles se heurterait Ie calcul effectif de ces esperances conditionnelles) les prerequisites sont prohibitifs. 11 faut , en effet, connaitre la totalite de la loi spatiale, dont l'inference statis tique (condition all n'est jamais possible en dehors du cadre de modeles particuliers (FA a loi spatiale gaussienne ou lognormale) rarement compatibles avec les donnees (condition c/).

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