Genetic Modeling of GIS-Based Cell Clusters and Its Application in Mineral Resources Prediction

This paper presents a synthetic analysis method for multi sourced g eo logical data from geographic information system (GIS). In the previous practices of mineral resources prediction, a usually adopted methodology has been sta tistical analysis of cells delimitated based on thoughts of random sampling. Tha t might lead to insufficient utilization of local spatial information, for a cel l is treated as a point without internal structure. We now take “cell clusters ”, i. e. , spatial associations of cells, as basic units of statistics, thus th e spatial configuration information of geological variables is easier to be dete cted and utilized, and the accuracy and reliability of prediction are improved. We build a linear multi discriminating model for the clusters via genetic algor ithm. Both the right judgment rates and the in class vs. between class distan ce ratios are considered to form the evolutional adaptive values of the populati on. An application of the method in gold mineral resources prediction in east Xi njiang, China is presented.

Theory and Method of Mineral Resource Prediction Based on Synthetic Information

Metallogenic prognosis of synthetic information uses the geological body and the mineral resource body as a statistical unit to interpret synthetically the information of geology, geophysics, geochemistry and remote sensing from the evolution of geology and puts all the information into one entire system by drawing up digitalized interpretation maps of the synthetic information. On such basis, different grades and types of mineral resource prospecting models and predictive models of synthetic information can be established. Hence, a new integrated prediction system will be formed of metallogenic prognosis (qualitative prediction), mineral resources statistic prediction (determining targets) and mineral resources prediction (determining resources amount).

Expert System for Statistical Prediction of Mineral Deposits on Middle and Large Scales

The expert system for statistical prediction of mineral deposits on middle and large scales takes the system of scientific exploration theories, criteria and methods proposed by Professor Zhao Pengda as the field expert knowledge. At present the developed system focuses on two aspects: synthetic exploration and quantitative exploration. Among the three basic theories for the prediction of deposits, it highlights the applications of seeking anomaly theory. This system is characteristic in the determination of geological background, the study of geological anomalies and the delineation of geological background, the study of geological anomalies and the delineation of mineralization anomalies. The system combines closely the knowledge base, method base and database .integrates the input and output information of multi - sources and mul-ti - variables , data , graphs and imagine processing system and inquiring system as a whole . So the system can meet in general all kinds of demands in statistical prediction of mineral deposits . Since the statistical prediction of mineral resources is a kind of systematic engineering pro ject , a further study should be carried out on the fields of theoretical exploration and ster eo - exploration on the basis of unceasingly perfecting the above-mentioned fields in order to establish a comprehensive intelligent system for scientific exploration , to provide new methods , new techniques and new ideas for fast prospecting appraisal of mineral resources .

Predictive GIS Model for Potential Mapping of Cu,Pb,Zn Mineralization

ABSTRACT The geologic features indicative of Cu, Pb, Zn mineral deposits in a area are fractures （structure）, and host rock sediments. Datasets used include Cu, Pb, Zn deposit points record, geological data, remote sensing imagery （Landsat TM5）. The mineral potential of the study area is assessed by means of GIS based geodata integration techniques for generating predictive maps. GIS predictive model for Cu, Pb, Zn potential was carried out in this study area （Weixi） using weight of evidence. The weights of evidence modeling techniques is the data driven method in which the spatial associations of the indicative geologic features with the known mineral occurrences in the area are quantified, and weights statistically assigned to the geologic features. The best predictive map generated by this method defines 24 % the area having potential for Cu, Pb, Zn mineralization further exploration work.

GIS Predictive Model for Producing Hydrothermal Gold Potential Map Using Weights of Evidence Approach in Gengma Region, Sanjiang District, China

Gengma region, Sanjiang district is known to have some large-scale gold deposits. GIS predictive model for hydrothermal gold potential was carried out in this region using weights of evidence modeling technique. Datasets used include large-scale hydrothermal gold deposit records, geological, geophysical and remote sensing imagery. Based on the geological and mineral characteristics of areas with known gold occurrences in Sanjiang, several geological features were thought to be indicative of areas with potential for the occurrence of hydrothermal gold deposits. Indicative features were extracted from geoexploration datasets for use as input in the predictive model. The features include host rock lithology, geologic structures, wallrock alteration and associated (volcanic-plutonic) igneous rocks. To determine which of the indicative geological features are important spatial predictors of area with potential for gold deposits, spatial analysis was done through the modeling method. The input maps were buffered and the optimum distance of spatial association for each geological feature was determined by calculating the contrast and studentized contrast. Five feature maps were converted to binary predictor patterns and used as evidential layers for predictive modeling. The binary patterns were integrated in two combinations, each of which consists of four patterns in order to avoid over prediction due to the effect of duplicate features in the two structural evidences. The two produced potential maps define almost similar favorable zones. Areas of intersections between these zones in the two potential maps placed the highest predictive favorable zones in the region.

Aspects of Regional and Worldwide Mineral Resource Prediction

The purpose of this contribution is to highlight four topics of regional and worldwide mineral resource prediction:(1)use of the jackknife for bias elimination in regional mineral potential assessments;(2)estimating total amounts of metal from mineral potential maps;(3)fractal/multifractal modeling of mineral deposit density data in permissive areas;and(4)worldwide and large-areas metal size-frequency distribution modeling.The techniques described in this paper remain tentative because they have not been widely researched and applied in mineral potential studies.Although most of the content of this paper has previously been published,several perspectives for further research are suggested.

A Preliminary Review of the Metallogenic Regularity of Nickel Deposits in China

The nickel deposits mainly distributed in 19 provinces and autonomous regions in China are 339 ore deposits/occurrences, including 4 super large-scale deposits, 14 large-scale deposits, 26 middle- scale deposits, 75 small-scale deposits, and 220 mineralized occurrences. The prediction types of mineral resources of nickel deposits are magmatic type, marine sedimentary type and regolith type. The formation age is from the Neoarchean to the Cenozoic with two peaks in the Neoproterozoic and the late Paleozoic. The nickel deposits formed in the Neoproterozoic are located on the margin of the North China Block and Yangtze Block, and those formed in the late Paleozoic are mainly distributed in the Central Asian Orogenic Belt （CAOB）, Emeishan and the Tarim Large Igneous Provinces （LIPs）. Magmatic nickel deposits are mainly related with broken-up continental margin, post-collision extension of the orogenic belt and mantle plume. According to different tectonic backgrounds and main characteristics of magmatism, the Ni-Cu-Co-PGE metallogenie series types of ore deposits related with mantle-derived mafic-ultramafic rocks can be divided into 4 subtypes： （1） the Ni-Cu-Co- PGE metallogenic series subtype of ore deposits related with mantle-derived mafic-ultramafic rocks in the broken-up continental margin, （2） the Ni-Cu-Co-PGE metallogenic series subtype of ore deposits related with mantle-derived mafic-ultramafic rocks in mantle plume magmatism, （3） the Ni-Cu-Co- PGE metallogenic series subtype of ore deposits related with mantle-derived mafic-ultramafic rocks in the subduction of the orogenic belt, and （4） the Ni-Cu-Co-PGE metallogenic series subtype of ore deposits related with mantle-derived mafic-ultramafic rocks in post-collision extension of the orogenic belt. We have discussed in this paper the typical characteristics and metaliogenic models for Neoproterozoic Ni-Cu-（PGE） deposits related with broken-up continental margin, Cambrian marine sedimentary Ni-Mo-V deposits related with black shale, early Permian Ni-Cu deposits related with post-collision extension of the orogenic belt, late Permian Ni-Cu-（PGE） deposits related with Large Igneous Provinces （LIPs）, and Cenozoic Ni-Au deposits related with regolith. The broken-up continental margin, mantle plume and post-collision extension of the orogenic belt are important ore- forming geological backgrounds, and the discordogenic fault, mafic-ultramafic intrusion, high MgO primitive magma （high-MgO basaltic magma）, deep magmatism, sulfur saturation and sulfide segregation are 6 important geological conditions for the magmatic nickel deposits.