The Research Of Digital Mineral Deposit Model & Development Of Metallogenesis Prediction System Of Fenghuangshan Copper Deposit

The Tongling region is one of the region that copper ore deposits were concentrated developed in our country. It locate in the middle of the Cu-Fe-Au multimetal mineralization belt of middle and lower reaches of Yangtze River. Its geotectonic evolution has gone through four stages: Pre-geosynclinal stage, Geosynclinal stage, Platform stage and Diwa stage by the analyzing of sedimentary formation, magma formation, metamorphic formation, structural styles & tectofacies and space-time orderliness of mineral distribution in this region and its vicinage. Every stage had its different metallogenesis. Among these, the strongest metallogenesis is the one which arose by Yanshanian magmatic processes in Diwa stage. The most ore deposits were formed during this magmatic processes in the region.Fenghuangshan copper deposit is one of the mainly deposit in Tongling ore deposits concentrated region. It lodged in the western contact strip of Xinwuli rock body. The occurrence of ore body was controlled by Xinwuli rock body, Triassic limestone, structure, especial the fragile dilatant fault structure which was formed in the same period of time with rock body. In the fragile dilatant fault structure belt, there are breccias generally which mainly include three types: brecciated granodiorite, brecciated ore and brecciated marble. According to thefractal analysis, its' fractal dimension of morphology and size distribution is 1.26,1.14,1.01 and 1.389,1.526,1.24. It indicated that, brecciated granodiorite was foemed mainly by chemical attack, brecciated ore and brecciated marble were hydraulic breccias which were formed mainly by mechanical process, and the energy when brecciated ore was formed is higher than the energy when brecciated marble was formed.During the research of tectono-geochemistry in the south part of Fenghuangshan copper deposit, it is discovered that the fractal character of Cu is multifractality, and different from each other according to the geological bodies. Compound with the distribution character of Cu in different geological bodies, it is illustrated that the metallogenesis which different geological bodies had gone through in this area is different, and the intensity of metallogenesis which quartzite monzodiorite had gone through is higher, and in favor of the concentration of metallogenic element.BP neural network technique is a in common used non-linear fit method now. Its function is that it provide a non-linear static mapping, and can gain upon a non-linear relation which discretionary imparted with a discretionary precision. It also has the learning and extending function. It can achieve the highly non-linear mapping from input to output by the coupling relations among neural cells. The formation and location of ore body is the output of the coupling of every factor of ore controlling. Itscoupling mechanism is difficult to fit with linear function. The highly non-linear fit function of BP artificial neural network can resolve yhis problem appropriately. Using eight known specimens of Fenhuangshan copper deposit, and putting its itto the network to learn, after more than 5000 iterativenesses, the network constringed and the error of output reached the requiration of precision. There fore, it is feasible that using the model of BP artificial neural network to fit the coupling among the factor of ore controlling during the ore forming process and the model of metallogenic prediction of this area is established by this way. The non-linear fit function of BP artificial neural network is achieved mainly by the connecting weights among the neural cells inside the network. And so, the connecting weight quantificationally show the weight which the neural cell influence next layer's neural cell. The influence weight from input layer's neural cell to output layer's neural cell can calculate by the running mechanism of network and the tracing weight of neural cell. Based on this weights, and compound with the exploring data of geophysics and geochemistry, the model of prospecting prediction of Fenghuang...