Permeability is an important petrophysical parameter used for the management of hydrocarbons in reservoirs. It controls hydrocarbon migration and dictates rates of withdrawal during production. For an apparently homogeneous sandstone reservoir, permeability can vary over several orders of magnitude, making it the most challenging petrophysical parameter to quantify. Despite tremendous advancements in well-data acquisition technologies in recent years, petrophysical determination of permeability remains problematic. This paper presents a robust and inexpensive method of using conventional log data to determine permeability, a method that has shown good matches to core data from different geological environments in many countries. The approach described here shows that the internal pore systems of clastic rocks can be modeled to simulate a load-bearing rock-frame filled with a non-load-bearing pore-filling matrix. The former lays the post-depositional foundation for permeability to exist, whereas the latter can adversely affect permeability in response to diagenesis. This paper demonstrates that for accurate quantification of the effects of diagenesis on permeability, the determination of permeability simultaneously with other petrophysical parameters is essential. To date, most models and techniques have merely been linear or non-linear curve fittings, or empirical approaches that rely on retrofitting permeability as a function of irreducible water saturation. The technique presented here determines permeability without prior knowledge of water saturation. The resulting permeability profiles have the same sampling rate as common log curves and can be compared easily with routine core analysis (RCA) results. Further, this technique can readily be adapted to assist 3D static modeling by providing up-scaled permeability predictions sorted by litho- or electrofacies groupings.
In recent years, subsurface static modeling has increasingly been accepted as the method of choice for assessment of hydrocarbon resources from exploratory drilling data, and for post-discovery field development.
