Abstract

In mainland China, there are large surface areas covered with shallow overburden (Regolith thickness < 100 m). Geological mapping is difficult here as there is not enough exposed bedrock. In this paper, we transfer geochemical and geophysical data to characteristics, and use it in geological mapping to identify the underlying bedrock. Above all, we define the “represent area of one geochemical sample” as one “statistical unit”. All geophysical data in each unit (hundreds of data) are analyzed generating statistical parameters, such as mode, interquartile range, frequency, skewness, and kurtosis, which are combined together to describe the characteristics of rocks in this area. As for the geochemical data in each unit, some rock-forming elements are screened to build new parameters, such as SiO2, Na2O + K2O, CaO, Al2O3, FeO + MgO. All geophysical and geochemical parameters are regarded as characteristics of one unit. The merged array is normalized so that all the parameters have uniform weight and the comparability between different parameters is improved. Then, K-means clustering method is used to classify all the samples in a research area. As the K-value is very difficult to estimate, it is necessary to conduct further experiments with different K-values, determine and explain the relationship between different classifications, and then identify the best classifications. Using the field information as a reference, one or more classifications are judged as one geological body. The method in this paper is practiced using the Tahe area, located within a typical shallow overburden area in Northeast China, as a case study. We used seven elements of 334 geochemical samples and 41.222 geological samples. K-values of 6, 7, 8, and 9 are calculated. We were successful in identifying geological bodies, and gained a new understanding on the scope of some rocks types. It is believed that the method proposed in this paper is highly efficient, easy to conduct, and can provide more detailed and comprehensive information than traditional methods.

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