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化探异常编号与异常评价自动化方法
引用本文:张茂忠,杨乐超,陈琦伟,等.化探异常编号与异常评价自动化方法[J].物探与化探,2014(2):396-401.
作者姓名:张茂忠  杨乐超  陈琦伟  
作者单位:重庆市地质矿产勘查开发局川东南地质大队,重庆400038
摘    要:异常编号与异常评价分级是化探工作量较大和专业性较强的工作,采用Visual Basic程序方法实现了异常编号与异常评价的全自动化,快速,准确,灵活,1 h内可完成3 600 km2的1∶5万化探数据处理。该方法先统计出不同地质单元的背景值,在程序运行时依据工作比例尺选择合适的搜索半径、点控制面积等参数。程序利用异常临时存储器搜寻每一个元素独立的异常,自动对异常进行编号并统计异常参数,再进一步找出各个组合异常。该方法输出结果有20多项,如各元素各个异常的首坐标、最大异常值、异常平均值、变异系数、富集系数、叠加强度、异常面积、组合异常的元素序列、异常重合度、综合异常评价分级指数等等。输出结果提供了较全面的异常信息,可灵活选择和创建新的异常评价分级指数。

关 键 词:地球化学  异常编号  异常评价  数据管理

THE AUTOMATIC METHOD FOR ANOMALY NUMBERING AND ANOMALY EVALUATION
ZHANG Mao-zhong,YANG Le-chao,CHEN Qi-wei,YANG Zhen-hong.THE AUTOMATIC METHOD FOR ANOMALY NUMBERING AND ANOMALY EVALUATION[J].Geophysical and Geochemical Exploration,2014(2):396-401.
Authors:ZHANG Mao-zhong  YANG Le-chao  CHEN Qi-wei  YANG Zhen-hong
Institution:( Chongqing Bureau of Geology and Mineral Resources Exploration & Development, Chongqing 400038, China)
Abstract:The anomaly numbering and anomaly evaluation classification reguire heavy workload and high technique. The Visual Basic program can realize full automation of anomaly numbering and anomaly evaluation. This method is rapid, accurate and flexible in that it can process geochemical data of 3 600 km2 on the scale of 1 ∶ 50 000 within one hour. Firstly, the Visual Basic collects the background value of different geological units. According to the working scale, it chooses suitable parameters such as search radius and point con-trols area during its operation. By using temporary memory, the program searches for independent anomaly of each element, automati-cally numbers the anomaly and works out the abnormal parameters, and finally finds out each composite anomaly. The output includes such items as the coordinate origin of the anomaly of each element, the maximum value of anomaly, the average value of anomaly, the coefficient of variation, the enrichment coefficient, the superimposing strength, the anomaly area, the areal productivity, the element sequence of each composite anomaly, the contact ratio of anomaly, and the composite index of anomaly evaluation. The output provides more complete information about anomaly for choosing and creating new indexes of anomaly evaluation classification.
Keywords:geochemistry  anomaly numbering  anomaly evaluation  data management
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