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DECISION MAKING USING GEOSTATISTICAL ANALYSIS: CASE STUDY OF A NI-SILIKAT DEPOSIT CIKATOVE E VJETER - KOSOVO
Abstract
Geostatistical analysis provides a powerfu l tool for enhancing the prediction and decision making capabilities of geologists and mine planners. The majority of practicing geologists are involved with mining and/or exploration ventures. As such a significant proportion of the geologist’s time is devoted to designing and impl ementing drilling and sampling progr ammes and using the resultant data to predict (and reconcile) reserve tonnages and qualities on a variety of scales, ranging from life-of-mine areas to daily production figures. This paper highlights the availability and benefits of some basic geostatistical techni ques for improving the results emanating from routine processing of geological data. The intention is not to provide a detailed re view of available geos tatistical techniques and benefits, nor to compare available so ftware packages. The aim is rather to summarize the those concerned with r outine manipulation of geological data, predominantly by applying tr aditional statistical methods , will be encouraged and empowered to take advantage of the benefits available from geostatistical analysis. Ni-silicate deposit of Çikatovë e Vjetër is one of the richest with Ni of this genetic type. Since ore deposit formation is almost always controlled by spatial factors, or paleorelief, results for adjacent points will generally show a degree of correlation. Geostatistical methods which are used for analysis are histograms, correlation analysis, experimental variograms and their models, surface variograms. From geostatistical analysis conducted for this deposit can make some conclusions about economic considerations. Considerations were taken into accoun t are: analysis of drilling program or drilling grid, optimi zation and designing drilling program, estimation of the thickness of ore body, variance estimation. The results of these analysis enable the determination of making decisions such making maps for the categorization of reserves, making variance of grade, thickness or another parametric set with a coefficient of error.
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References7
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