Multivariate Statistical Analysis Applied And Studied In Nuclear Survey Data Processing

With the increasing demand for mineral resources the present situation of mineral resources in China is very serious. To change this situation, we must actively explore new effective data processing method in order to increase mineral resource of exploration over all and increase the reserves of mineral resources for our economic security and efficiency to resources to ensure sustainable development.In the resource exploration, the spatial distribution of element content is extremely complicated. With exploration work to deepen, in addition to methods and techniques, the traditional method of data processing more and more to show limitation, so in addition to new methods and new application of technical means, the search for new efficient data processing methods to extract more useful information has become the pursuit of exploration target.Anomaly in the survey data processing and interpretation of inference work, increasing use of various statistical methods, such as trend surface analysis, multiple regression analysis, discriminant analysis, factor analysis and cluster analysis to improve the level of exploration results and forecast Promote the development of survey work, in Si-Chuan Province.The paper is to transfer homes to carry out gold exploration projects which is based on multivariate statistical analysis of survey data processing for nuclear applied research. X-fluorescence analysis, the main measure of gold may be associated with the element content, such as:Fe, V, Ti, Ni, Zn, Pb, Cu; single element of each element processed by the content of the element distribution maps, and the elements Simple correlation with the degree of the element of gold; on this basis, cluster analysis and multiple regression analysis, gold and other elements of the relationship, to use one or another element is difficult to predict the content of the element (Au) Content, which is used to create a new exploration leads; through trend analysis, and further refine the information hidden in the samples to reveal the information hidden in the data, reflecting the different geological characteristics of the body caused by field halo.