EXPORTING PETROPHYSICAL PROPERTIES OF SANDSTONES FROM THIN SECTION IMAGE ANALYSIS

摘要

Estimation of the petrophysical properties using imaging techniques and image analysis has been an active area of research in recent years. This has been primarily focused on 3D imaging and subsequent modeling of formation properties, termed Digital Rock Physics. This work requires an intact sample of material. When sample type or quality are not sufficient for 3D imaging, or where cost is prohibitive, modeling of petrophysical properties using thin section images is a viable, and for some samples, a superior alternative.This study involves the use of transmitted light image tiles from the light microscope. Each thin section is scanned in plane, cross-polarized, and fluorescent light. Each of these provide information about the framework and authigenic phase mineralogy. The advantages of thin section imaging for estimating petrophysical properties, include the ability to identify framework grain types for provenance and reservoir quality modeling studies, differentiation of detrital and authigenic phases, and establishing paragenesis.We apply a Carmen-Kozeny type model to thin section images of samples for which laboratory measurements of porosity and brine permeability were made. This has allowed us to model absolute permeability to within a factor of two for sandstone samples having laboratory-measured permeabilities ranging from 175 mD to 8D, and builds on a calibration data set of approximately 30 samples. For the original data set, modeled permeability agreed with measured permeability to within a factor of two, over a range of permeability from 8mD to 3D.A key input parameter to this model is an estimate of specific surface area. The 2D estimate of specific surface area, defined in Hathon, et al., (2003), is the ratio of the total porosity perimeter to the total area analyzed. The normalization to the total area analyzed, allows the number of image tiles analyzed to be varied for each sample. The estimated specific surface area is a function of image magnification, down-sampling and filtering of the image are applied during analysis. This work extends the previous model by adding a fractal analysis to the estimate of specific surface area. This allows us to account f o r the impact of magnification and processing when modeling permeability from 2D image data. Total porosity from 2D image segmentation agrees towithin +/- 2% of laboratory measured porosity.Future work includes developing a model for converting 2D pore body size distributions to 3D equivalents for comparison to NMR based estimates of pore body size, together with calibration of the surface relaxivity term. We also intend to investigate the relationship between the estimated tortuosity in thin section and Formation Factor, and estimating pore throat size distributions for modeling Mercury Injection Capillary Pressure (MICP) data.