MAP: A method of multiattributive prognostication of mineral resources estimation

Abstract

The analytical process of prognosticating mineral resources on a particular terrain is based on the recognition of different indicators, namely, features (geological, geochemical, geophysical, etc.) as well as on correlative binding to a certain type of deposit and metallogenic environment. Prognostication is grounded on the very concept of balance, which means a definition of the overall relative significance of groups of features (attributes), and relies generally, within this process, on both geological information on the characteristic features of mineralization and information on specific features for the particular type of deposit and metallogenic environment. This may be reached by structuring a prognostication problem, the solution of which requires the involvement of several persons (experts) aiming to define objectively the criteria to determine the degree of significance of attributes, generalize preferences for a single group of attributes, state precisely a composite-normalized vector of estimation, and define the ranks and composite vectors of prognostication. In principle, prognostication is an extremely complex process due, as a rule, to a fuzzy nature of indicators, the incorporation of numerous attributes and complex correlation bonds. This leads to the conclusion that it is impossible to automatize completely the process of prognostication using mathematical-modelling and computerization, and that a pragmatic solution of the problem should be found in a hybrid approach by combining expert knowledge and logistic support offered by mathematics and computer technology. These are the basic principles of the Method of Multiattributive Prognostication, abbreviated to MAP, which is presented below.