Abstract
We present a large-scale study of the relationship between dense airborne SkyTEM resistivity data and sparse lithological borehole data.Airborne electromagnetic (AEM) data contains information about subsurface geology and hydrologic properties; however extracting this information is not trivial. Today, geophysical data is used in combination with borehole data to create detailed geological models of the subsurface. The overall statistical relationship is, however, not widely known. The objective of this study is to develop a method for understanding the relationship between petrophysical properties and lithology, and apply this to get a better understanding of large-scale petrophysical structures of the subsurface.The data sampling is carried out in a scheme where data is interpolated onto the position of the boreholes. This allows for a lithological categorization of the interpolated resistivity values, revealing different distribution functions for lithological categories.A very large and extensive dataset is available in Denmark through the national geophysical and borehole databases. These databases contain all geophysical and borehole data in Denmark and covers a large part of its surface. By applying the proposed algorithm to all available airborne electromagnetic data, detailed maps of the large-scale resistivity-lihology structures on a National scale in Denmark are constructed.
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