| Locating and quantitative prediction of Fe mineral deposits of solid mineral resources by the theory & methods of mineral resource prediction with comprehensive information is carried out nationwide in China at scaling 1:5,000,000. The technical route and research method of locating Fe mineral deposits and principle of compiling attribute table of independent variables and functional variables are proposed. Upon methodology study, the qualitative locating and quantitative predicting mineral deposits are carried out with linear regression and characteristic analysis, and enclose perspective area of Fe mineral resources. 1 Tasks and technical methods of the quantitative prediction 1.1 The tasks of research The distribution of the large and super-large deposits concentrated regions is "a Triton of the minnows". At an angle of deposit aggregation, the large and super-large deposits is the minority, but its reserves is huge. It is "Triton"show, and not only one; the medium and small sized deposits are the majority, and its reserves are little. They are "minnows"show. The super-large, the large, the medium and the small deposits all constitute "the deposits concentrated regions". At first, according to different minerals to construct the deposits concentrated regions, they are usually correlated to anomaly distribution area of main metallogenetic element, and there are explicit boundary conditions and their domain. From analysis of the geological evolvement, they are usually metallogenetic provinces that are composed of three and more metallogenetic epoch or deposits types. Secondly by the deposits concentrated regions to construct deposits model, and by the anomaly concentrated regions to construct prediction model. they both belong to statistic model, it study the commonness of the deposits and anomaly concentrated regions. The prediction of mineral is based on analogy theory and seeking anomaly theory, and seeking anomaly is used to estimation. The knowledge database is constructed on basis of the original database of geology, geophysics, geochemistry and remote sense. The original database is the scale of the data itself. It aims to responding to data source, data quality and data share. The knowledge database is database of research goals and domination goals, it is responding to causality between the data, its purpose is decision making analysis on GIS platform. Regarding the deposit concentrated regions as unit, the map-layer is built, the unit is parted, the attribute table is complied. The attribute table will come into being operation matrix by reasonable variable evaluation. By researching Ore control factor of the deposit concentrated regions, various ore control factor-layer come into being, and the relevant attribute table is compiled. It may evaluate the favorability of every ore control factor by variable evaluation. The deposit concentrated regions is the response variable map-layer, the ore control factor-layer is the variable map-layer, they are causality. The statistics prediction of deposit concentrated regions is locative prediction, the mineral resources prediction of the large and super-large sized deposit concentrated regions is quantitative prediction. 1.2 Technical methods In the prior of geology theory, Regarding geological body as unit, their information of geology, geophysics, geochemistry and remote sense is studied from geological evolvement, and the interpretation of synthetic information is processed, and the map group of mineral resources prognosis of synthetic information is compiled. Then the unit is parted, the variable is filtered and evaluated. And then filtering the model unit and the effective variable, at last, constituting the seeking minerals model and prediction model of synthetic information. The key is studying the transform orderliness among information. It aims to using anomaly concentrated regions to predict deposit concentrated regions. Metallogenic prediction, statistics prediction and mineral resources prediction is unified. From the viewpoint of statistics, the series geological map are the sets of geological bodies and deposit concentrated regions of different characters, ages, grade and depth. Information of geology, geophysics, geochemistry and remote sense is the displays of different sides of geological body and the large and super-large sized deposit concentrated regions, In fact, the information is the multidimensional scale to them. It aims to recognizing the geological bodies and the deposits concentrated regions by the 3-D of geological bodies. The mineral resources exist as geological carrier, it is the mineral resources body. The size of mineral resources body is different. The super-large, large, medium and small sized deposits set is solving a problem of the ascending and well-ordered variables from the statistics viewpoints. The prediction key is studying the ascending and well-ordered variables of the deposits set and ore-controlling factors. Parting unit and compiling attribute table of every map-layer will form generalized matrix. By selecting reasonable mathematical model, microscopically research well-ordered variables. 2 Partitions of map-layers for mineral resources prognosis 2.1 The map-layer of the Fe deposits concentrated regions. The map-layer of the deposits concentrated regions is the map-layer of researching target. By synthetic interpretation, on the basis of the mineral distribution map to define the deposits concentrated regions. From the well-ordered variables to compile attribute table and research the order of the set of the deposit concentrated regions enrich how to enrich. 2.2 The map-layer of geological body. It is divided into the Early Sinian basement, the strata of various ages, rock body and gravity and magnetic structure, and paring the unit to every map-layer. By the will-ordered variables to study the attribute table, and research the metallogenic favorability of different mine, and part the grade. 3 The compilation of attribute table of independent variables & functional variables 3.1 The principle of compiling the attribute table The constructing of attribute table should link tightly to prediction map group, and is to assess mineral resources quantitative based on synthetic information. The table can transform a calculating matrix by logically assigning their value, its rows are the sample numbers of units, and the lines are the variable numbers. The unit parted, extract of variables and assignation of their values are implemented in each map-layer. We can build up prospecting model and statistical model based on synthetic information from the map-layer group, and accomplish decision-making analysis at GIS platform. The objects would be put in order according to their metallogenic advantageousness. The result in the formation of orderly variables that can be utilized in prediction of large and super-large sized deposits. 3.2 The compilation of attribute tables of functional variable layer-map group The mineral prediction based on synthetic information is quantitatively statistical with geological entities as units. The geological entities appear in different grades, and the deposits and their corresponding basins are the most basic units. The deposits concentrated regions and their corresponding basins are larger units where there are maybe large and super-large deposits. The prediction of large and super-large sized deposits regards deposits concentrated regions as model units, the anomaly concentrated regions and their basin assembles as prediction units. 3.3 The compilation of attribute table of independent variable layer-map group We part the map-layer by ore-controlling map group, and part the units of various map-layer by the differences of the metallogenic favourability of ore-controlling factors, and compiling the attribute tables of various unit. By the different object of prediction mine, the metallogenic favourability of the units must separately be ordered . 1 Basement layer-mapsThe basement control the cover and the rock body, and it has metallogenic specialization. The relations between the basement and the other ore-controlling factors is very important in prediction. 2 The map-layer of the rock body The units are parted with the circular structure of gravity and magnetic vertical second derivative of different upward continuation heights and the distribution disciplinarian of the exposed rock body. 3 The map-layer of the structure Mostly studying that gravity and magnetic structure framework controlling the objective minerals, it is the foundation of studying tectonic ore-controlling. The standard of compiling attribute tables is that the attributes must be closely correlative to the map-layers, and map-layers is correlative too, its objective is to predict the mineral resources of synthetic information. 4 The potential assess of Fe mineral resources On the basis of the statistics prediction of the Fe deposit, the mineral resources prediction is processed, if the I grade unit of the statistics prediction be satisfied, in the same time the resources quantitative scale is super-large, then this unit is I grade metallogenetic perspective area; if the resources quantitative scale is large, then it is II grade metallogenetic perspective area; if the statistics prediction is II grade unit and the resources quantitative scale is super-large, then this unit is III grade metallogenetic perspective area; if the statistics prediction is II III IV grade unit and the resources quantitative scale is large, then this unit is IV grade metallogenetic perspective area. Through the metallogenetic perspective area ,it can be seen that there are 25 I grade metallogenetic perspective areas , 8 II grade metallogenetic perspective areas , 40 III grade metallogenetic perspective areas and 75 IV grade metallogenetic perspective areas , the general resources quantitative separately is 75.6 billion tons, 3.4billion tons,8.3 billion tons and 6.9 billion tons. The resources prediction gross in Fe concentrated deposit regions can reach 62.3 billion tons through prediction in China, and the general resources potential is 62.3 billion tons. These Fe deposit resources what haven't been proved up are mostly locate in the main Fe deposit metallogenetic region belts in the middle-west and the east part of China, such as AnbenPanxi Jinbei Mengzhong areas. In the east part of China ,due to the high exploration degree , the prediction resources mostly distribute in the depth or circumjacent of the known mineral belts by insidious mineral and blind mineral ; and the exploration degree is lower or very low, so there is a big development foreground in the middle-west area . 5 Conclusions Some new achievements and understand have been acquired through collecting and synthesis studying on the data. The performing of this work provided systemic data evidence for further develop the bigger scale Fe metallogenetic prediction , then develop Fe deposit exploration better. [1] From the distribution map of national Fe deposit, it can be seen that the distribution of Fe deposit is compression. The large super-large Fe deposit and the medium small sized Fe deposits compose deposit concentrated regions, and take on the distribution form of "a Triton of the minnows". For example Anshan Benxi Shuichang BaiyuneboPanzhihua Fe deposit areas all have this feature. [2] According to the gravity circularity structure and the exposed basement map of China, we...
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