Predicting Petro-physical Properties using SEM Image

摘要

The permeability estimation of reservoir rocks using numerical methods has always been a challenge for petrophysicist. Several models have been developed for its computation of this parameter. As the permeability is entirely controlled by the geometry, the possibility arising of estimating the permeability from quantifiable attributes of the space has always has been a approach. In the present paper, a model is discussed which gives accurate prediction of the permeability based on two dimensional SEM image of a core sample of sedimentary rock. The inputs required for the model are the areas and perimeters measurements from the images of space. The individual conductances are estimated using hydraulic radius approximation. Before using the data obtained from images, stereological corrections are used to convert geometries and various hydraulic corrections are used to account for converging-diverging flow paths. Kirkpatrick's medium approximation is finally used to find the value of the hydraulic conductances of the individual pores. The method has been applied to six data sets of SEM images which include Berea sandstone, consolidated sandstones and carbonate samples. The laboratory determined air permeabilities of these samples ranged from 0.5-400mD. The permeability values predicted by this method are within a factor of two of the values. This method requires least data manipulation and computation and is more accurate than conventional methods such as the Kozeny-Carman equation. The method holds promise of permeability predictions on irregular rock samples like drill cuttings which cannot be in standard lab measurements. Another possible future is to use down-hole borehole imaging technology to provide an image with the appropriate resolution, thereby allowing in-situ permeability estimation, without the need for core samples. Keywords Permeability, Scanning Electron Microscope, Pore Network Modeling, Porosity, Conductance, Sandstones and Carbonates