Reservoir permeability is one of the important parameters derived from well test analysis. Small-scale permeability measurements in wells are commonly made using core plugs or, more recently, probe permeameter measurements. Upscaling of these measurements for comparisons with the permeability derived from drill stem tests (DSTs) can be completed by statistical averaging methods. DST permeability is commonly compared with one of the core plug averages: arithmetic, geometric, or harmonic. Questions that commonly arise are which average does the DST-derived permeability represent and over what region is this average valid! Another important question is how should the data sets be reconciled where there are discrepancies? In practice, the permeability derived from well tests is commonly assumed to be equivalent to the arithmetic Cin a layered reservoir) or geometric Cin a randomly distributed permeability field average of the plug measures. These averages are known to be members of a more general power-average solution. This pragmatic approach (which may include an assumption on the near-well geology) is commonly flawed, owing to several reasons that are expanded in this article. The assessment of in situ reservoir permeability requires an understanding of both core (plug and probe) and well test measurements in terms of their volume scale of investigation, measurement mechanism, interpretation, and integration. This article presents a comparison of core and well test measurements in a North Sea case study. We undertook evaluation of three DSTs and associated core plug and probe data sets from Jurassic fluvial channel sandstones in a single field. The well test permeabilities were generally found to differ from the core estimates, and no consistent explanation could be found for the group of wells. However, the probe permeameter data were able to further constrain the core estimates. This study highlights the uncertainty in effective in situ reservoir permeability, resulting from the interpretation of small (core) and reservoir (well test) scale permeability data. The techniques used are traditional upscaling combined with the Lorenz plot to identify the dominant flowing interval. Fluvial sandstones are very heterogeneous, and this exercise is instructive in understanding the heterogeneity for the guidance of reservoir models in such a system.