THE REV CHALLENGE – ESTIMATING REPRESENTATIVE ELEMENTARY VOLUMES AND POROUS ROCK INHOMOGENEITY FROM HIGH RESOLUTION MICRO-CT DATA SETS

摘要

Micro Computed Tomography(μ-CT) imaging forms a great method to investigate internal rock structures – e.g.the void space,fluid distribution,etc.– fast,in three dimensions and non-destructively.Since the last decade,μ-CT has progressed to faster imaging as well as to faster reconstruction times,and especially to high quality image resolution and sharpness(in the micron or even sub-micron range).With this,access is granted to the investigation of small pore space features(e.g.clay induced porosities or porous networks,formed by dissolved mineral phases) as well as to representative,i.e. predictive fluid flow modeling.Although modeling of fluid flow through small sample networks may increase the knowledge of fluid dynamics on a microscopic scale, representative modeling of physics remains the most important task.For this,porosity has proven to be the parameter of choice to characterize a porous media by terms of fluid dynamics and to determine a representative elementary volume(REV) for it.The REV is reached,when the average porosity in the probing volume becomes independent of the size of the volume.Nevertheless,this approach does not consider sample inhomogeneities or directional porosity variations,e.g.caused by layering effects.Hence, the author would like to present an advanced method to estimate representative elementary volumes derived by high resolution μ-CT imaging.This Method is based upon a variance analysis of directional micro-porosity logs,which have been calculated from 3D image quantification analysis.Additionally,a new method to estimate the sample inhomogeneity – as a quality control feature for the REV estimation – is introduced.With this analysis,it is furthermore possible to investigate scale,i.e.REV edge size,dependent structural effects and transitions.