Evaluation Of Geochemical Anomalies Based On The Multiple Element Data Fusion

Exploration Geochemistry has got a significant development over the past few years as an advanced prospecting method with both high efficiency and remarkable performance, which has been applied in different phases through the geological work and became an indispensable method. It has the advanced features of lower operation cost, wider area measurement and larger number of anomalies, and also has the ability of selecting the prospective metallogenic area and narrowing down the targeted region. The key point of exploration geochemistry is “Anomaly Evaluation”, a traditional approach is through analyzing the mathematical statistics of a single element(also called as single element calculation method), or depending on personal experience, and then using the anomaly map of single element and the integrated anomaly map made of the combination of various single element maps to guide the mineral prospecting.Since the 20 th century, duo to improved degree of geological works, shallow rich mineral resources has been exhausted gradually, and the exposed mine and surface occurrence mine are becoming less and rare recently, which lead to the result of a sharply growing difficulty in geological prospecting. Thus, future prospecting targets would be nothing but the left low grade mineral resources and concealed mine deep in the earth, where the traditional “High-Large-Comprehensive” geochemical anomaly evaluation method could not be used any more because of its low finding probability. In this particular circumstance, higher requirements would be needed for the geochemical exploration and anomaly evaluation. On the other hand, benefited from the development of computer technology, especially the extensive use of Geographic Information System(GIS) software, the efficiency of data processing in the geochemistry exploration has improved, where the raw input data can be easily translated into geochemical exploration achievement figures as single element anomaly isoline map in the computer. However, in practical works, this efficient method of drawing anomaly map by computer meets several problems such as loss of guidance duo to large area of anomaly occurs, and no regular rules to conclude and follow, and also too difficult to check and certify the anomalies. Although, in the recent years, “Multivariate Geological Information Integration Technology of Geology-Mineral-Geophysical-Geochemistry-Remote Sensing” has got tremendous development and wide application, and ore prospecting based on the “Module Combination” of different geochemistry exploration methods has also made some progress, litter research has been done on the data fusion of various single element geochemistry essential data.The paper researches into four 1:50,000 regional mineral survey area including Alshan region of Inner Mongolia, and on the basis of sufficient gathering of past geological and geochemical data, we carries out 1:5,0000 geochemical soil survey in 1,387 km2 region, and collects 8,316 samples, and also analyzes 116,424 elements. Each element has been analyzed by means of statistical analysis method including normal distribution measurement, data homogenization and “R” cluster, and then though a comprehensive analysis of the different and relationship of the elements, we establish an anomaly analysis model based on “Evidence Weighted” multivariate data fusion. In the paper, in order to achieve the aim of rapid, accurate judgment on anomalies, we take Cu element analysis as an example, and make Pb, As, Ag, Au, Hg as auxiliary elements for data fusion process. The research processes the geochemical exploration data mainly on the following two aspects. The first one is data fusion processing of anomalies according to the correlation of different elements to enhance the signal strength and achieve information complementary, and also solve the problem of insufficient information with single element. Another aspect is to redo the mathematical statistics analysis after data fusion in order to improve the lower limit of anomalies so as to remove redundant information and reduce effect of the interference factors. The anomalies after data fusion has better performance on reproducibility, accurate positioning and indicating direction of the ore region. We has also achieved good results benefited from the comprehensive of geochemical anomalies. In conclusion, geochemical anomaly evaluation based on the multiple element data fusion meets the demand of development of multivariate information integration, and also conforms to the objective evolution of “One Map” management and “Big Geology, Big Data” era.