The Geochemical Anomalies Delineated Methods Contrast Research

Long-term practical experience shows that geochemical exploration is a high-precision,high-efficiency prospecting method.And how to effectively and effectively extract mineralization anomaly information and rapid screening of mine anomaly is the key to determine this work.Geochemical background and abnormal division of the lower limit of the determination of abnormal geochemical exploration in mineral exploration is an important part of the purpose is from a large number of geochemical data extracted with the mineralization-related geochemical information.The Chengde area is the main output area of ??gold,silver,copper,lead and zinc deposits in Hebei Province.It is located in the Oulonggou-Shanghuangqi polymetallic metallogenic belt and is well-developed in metallogenic conditions.There are many large and medium-sized deposits,such as Beichagoumen Lead-Zinc Mine,Sadigoumen Molybdenum Mine and Niuquan Silver-gold Mine,and many small polymetallic mineralization sites,such as the Chuangwanggoumen Gold Mine.In this paper,the method of using the traditional statistical method,the 85% frequency method and the trend surface method to delineate the anomalies of ore-forming elements is introduced and analyzed with the example of the sediment data of 1:10000 in the Xiaowopu area of ??Fengning,Chengde.In this paper,we first calculated the characteristics of 2672 geochemical data in Xiaowotu area,Fengning,and analyzed the correlativity of each element.By R point group analysis and factor analysis,we found that Pb,Mo,Cu and Ag have good correlation.(Average + 2 times standard deviation),85% cumulative frequency method and trend surface method were used to analyze the influence of Ag,Pb(superscript 2 +)and Pb(superscript 2 +)on the geochemical data processing methods.,Zn three elements were delineated abnormal.It is found that Zn element is well delineated by frequency method,Ag element anomaly is well delineated by trend surface method,while Pb element anomaly is better by traditional statistical method.