Extraction Of Geochemical Anomaly Information Based On Compositional Balance Analysis

Geochemical data,as an important source of data information,plays an extremely important role in the abnormal extraction of mineralization information and prospecting practices.One of the keys to deal with these huge geochemical data is to mine the intrinsic relationship between geochemical data and various geological phenomena,to achieve quantitative inversion of mineralization information,and to provide intuitive data model for mineralization prediction and geological exploration by using of scientific methods.However,in the process of data processing,traditional multivariate statistical analysis methods often ignore the influence of the closure effect of compositional data,and directly process the data,making the results of data processing lack accuracy and scientific.In order to solve this problem,Log-ratio Transformation Algorithms have been proposed to eliminate the closure effect of compositional data.However,the application and feasibility of those various methods are still controversial internationally.Based on the measured data of the East Tianshan Mountains in Xinjiang,China,this paper demonstrates a new method of Compositional Balance Analysis(CoBA),by comparing with the isometric logarithmic ratio transformation method,the paper demonstrates that the method is feasible and effectivein in the field of sediment geochemical data processing and anomaly information extraction.The research area,Dongtianshan metallogenic belt is located in the Xinjiang Uygur Autonomous Region of China,which is famous for its copper and gold productions.It experienced a long history of tectono-magmatic activities which result to widely distributed igneous rocks.There are many deposits with huge resource potentials.In order to correctly identify the anomalous patterns related to iron ore mineralization and fractures from the geochemical data,14 kinds of elements,including titanium(Ti),vanadium(V),iron(Fe),copper(Cu),cobalt(Co),nickel(Ni),phosphorus(P),chromium(Cr),manganese(Mn),zinc(Zn),arsenic(As),gold(Au),mercury(Hg),strontium(Sb)were analyzed with CoBA method.The study constructed 13 balances that characterize different geological factors such as ore andfracture,and selected key information for further research.Compared with the results of iron ore and fracture extracted by the principal component analysis method based on the Isometric Log-Ratio(ILR)transformation,the CoBA method can not only analyze the elemental data by establishing an appropriate elemental analysis model,but also eliminate the closure effect of data,scientifically and objectively analyze the true relationship between elements,and intuitively model different geological elements,thus enhancing the anomaly information and suppressing the background information.Practice has proved that,the CoBA method can effectively interpret the geochemical data of sediments in the East Tianshan Mountains of China.