The Research On Application Of Quantitative Prediction Based On Prediction System Of Comprehensive Information Mineral Resources

The quantitative prediction of mineral resource is the use of computer andmathematical knowledge on the geological issues, causing the mineral resourceforecast to be more effective, objective and accurate. It unifies the geology andmathematics, information technology, the computer technology. It is thequalitative forecast deepening and the concrete application and it represents thedirection of development of resource forecast. With the difficulty of discoveryof mineral resources being increasing and the development and penetration ofthe theory and methodology of modern science and technology, themineralization forecast and the mineral resource appraisal theory, methods andtechniques has made substantial progress. With the nonlinear physics, statistics,spatial statistics, computer technology, spatial information sciences, and otherrelated specialties being cross-penetration, mineral resource evaluation alreadydevelop from the traditional simple analogy to the use of integrated informationwhich are oriented to the syncretizing of the comprehensive and complexgeology data.The quantitative forecast results can be used as the basis for thedeployment for exploration, reduce the risk and blindness, increasepredictability, thereby enhance the efficiency of exploration work. Therefore,all countries are taking deposit quantitative prediction very seriously.The quantitative prediction must take the basic geological understandingand the mineralization rule as a premise.The author starts with the geologicalbackground and known deposits (points), and then analyzes metallogenic rulesand factors. On such basis, the author interprets synthetically the informationincluding geology, geophysics, geochemistry, and remote sensing from theevolution of the geology and puts all the information into one entire system ofsynthetic information interpretation. On such basis, different grades and typesof mineral resource prospecting models and predictive models of syntheticinformation can be established. Hence, a new integrated prediction system will be formed of metallogenic qualitative prediction, mineral resources statisticprediction and mineral resources amount prediction. Based on computertechnology, the system is developed to carry out quantitative prediction ofsynthetic information.The cluster analysis is the multivariate statistical analysis methods which isbased on various index for digital classification. In recent years, it issuccessfully used in the classification of rock and paleontology, thedemarcation of stratum, the unusual ore-bearing evaluation and so on.According to the different object classification, the cluster analysis can bedivided into two kinds: one kind carries on the classification according to thevariables (index or geological character s) to the specimen or the sample, whichis called Q-cluster analysis; the other kind carries on the classificationaccording to the variable values which are observed on various specimens to thevariable, which is called R-cluster analysis.The abundance estimate is the quantitative evaluation method which isaccording to the ore body secondary dispersion halo to the ore body and it is inthe use secondary corona result and unifies the geological data to select thesecondary dispersion halo. Usually studied the metal quantity the correspondingrelationships between some horizontal section (or parallel to the slope of thesection) on contained with initially in this level ore body contained to carry onthe resources estimate.The Weighted abundance forecasting model aims at need of large-scaledeposits (body) target quantitative prediction and evaluation of the resources, isaccording to the earth's crust element being exceptionally or concentrates themineralization in the local area. At first, according to the size, grade and thecorresponding changes in the law abnormal size and density of known deposit,define benefit mineralization and concentration coefficient, and extrapolate tothe statistical anomaly ore-forming units and forecast correspondingly quantityof mineral resources of unknown target. The author uses the integrated information system on mineral forecastsynthesis to carry on 1: 200,000 scale silver mineral prediction in the east ofInner Mongolian and research the result.In an area with lower degree ofprospecting where model units are extremely few, the author interpretssynthetically the information including geology, geophysics, geochemistry, andremote sensing from the evolution of the geology, introduces the abundanceestimate approach, cluster analysis and weighted abundance in the predicting ofsilver reserves potentiality. By comparing the different predicting results and acomprehensive evaluation, the reliability of the predicting results has beenconcluded.The dendrogram of cluster analysis is more intuitionistic, which cancomprehensively utilize the multi-variables of geology, physical exploration,geochemical exploration and remote sensing to sort the samples, and the resultis more comprehensive and logical than traditional sorting methods. Theabundance estimate approach is more applicable in the area with similarmineralization law and in the analysis of element content in the form of oreminerals. Weighted abundance approach is suitable for the quantitativeprediction in a target area with multi-mineral mineralizing series. When themodel units in the research region are few, which one of the above predictingmethods is to be used lies on the amount of available datum of the researchregion. If the information of geology, physical exploration, geochemicalexploration and remote sensing is complete, cluster analysis can be used, to beverified with the other two methods at the same time. In a word, the key of thequantitative prediction of mineral resource is a thorough understanding of themodel units, and the statistical parameters should best represent the maincharacteristics of the research region units.