The Methods Of Processing,Analyzing Geochemical Element Data From Marine Surface Sediment And Evaluating Multivariate Information

Geochemistry of surface sediments at seabed is the main content of resources and environment research, and is an important scientific means to explore the resources and environment of the seabed. Based on mathematics geology methods and information processing principle, the article investigates relative technical links of elements geochemistry datum from Bohai surface sediments element geochemical environment evaluation project, and proposes a system approach of data processing fitting marine surface sediments geochemical environment evaluation.After the methods are analyzed, adjustment is proposed, and combining the datum of Bohai experimental area practical application based on adjustment is shown. Standardized method can eliminate difference of “Multi‐source data system error” and integrate the data that have difference into a map. But this method could only reflect distribution changes of samples and ignores the real level of element content; Adjacent points method regulates the data in a more reasonable range of assessment while narrows system error spacing. The article, on the basis of adjacent points method, applies adjustment processing to analyze the major elements and trace elements of Bohai multiple sources surface sediments geochemistry.Kriging and CoKriging method model are introduced. The building of these models, simulating of variogram and the usage of them is systematically analyzed. The experimental variogram of Fe, Ni, Co, and grain size parameters are calculated, and the theoretical fit is made to extract the parameters of the variogram function and of cross‐variogram function; The variogram function reflecting self‐correlation and co‐correlation of elements space, which prove that the Fe, Ni, Co and particle size not only has a significant statistical correlation, but also has a significant spatial correlation. The variogram Simulation results show that these parameters are subject to north‐north‐east‐trending tectonic framework. Using CoKriging on interpolation effect on boundary effect data and sparse data, the results show that the method reduce the estimation error and improve the interpolation results by synergistic interpolation of secondary variables in the cases of missing data information at boundary and data point sparse. In addition, the article describes the application of Kriging and CoKriging on the ARCGIS platform.Abnormal division method such as fractal, mutations boundary, flow accumulation and moving average is introduced, and with this method the Bohai geochemical elements abnormal division is worked out. The application results show that fractal, from the spatial self‐similarity of the geochemical field, divide the study area into different abnormal regions and abnormal levels, while delimite abnormal lower limit; Flow accumulation method guarantees comprehensively setting out abnormal regions, highlights weak anomaly and also the higher value area and linear features in high value clustered regions, when the abnormal regions in smaller area is delineated; Mutations boundary method delineate the similar abnormal regions as he moving average method, but the former identify more micromesh and objective abnormal areas than the latter method which has more human factors in application.Finally, comprehensive analysis method of multi‐information is introduced to superimpose information layers of geo‐chemical elements, abnormal distribution, structure, topography, geomorphology, gravity anomalies and magnetic anomalies, and to analyse correspondingly. The results of analysis and solving indicates that (1) different methods of extracting space abnormalities compensate for each other. Different methods of extraction, the geological environment indicated;(2) combination of spatial anomalous field distribution and other comprehensive information provide more environmental information.(3) there is strong or weak correlation among Zn(representing geochemical elements) abnormal distribution, surface sediment grain size abnormal distribution, bathymetry anomalies lies and Bohai tectonic environment characteristics.(4)the mainly controlled factor of Zn anomalies is grain size of surface sediments, and the secondary factor is gravity anamalies which contribute less for Zn abnomalies. In different target domain, relevance of grain size and Zn is different, the accuracy of the linear model simulation different also. In oil basins in the centrol Bohai, the grain size is obviously the main control variable, strong correlation with Zn content, and the simulation results of the linear model being of highly similar with its actual distribution, the similarity coefficient0.79; for region simulation, grain size contribution and linear simulation accuracy are higher compare with other target region because of containing most simulation units, which incicates that Zn content is strongly controlled by granularity in area near the shore; by contrast, the simulation result of Bohai tectonic basin and the tectonic zone has low accuracy comparatively, the correlation between granularity and Zn turned weak relatively, while gravity anomaly affect becoming stronger; in Zn linear anomaly region, model simulation accuracy being the lowest, and granularity contributing less, which indicate that Zn content relates to other factors in addition to granularity in Zn linear abnomaly region.