Elastic property‐porosity relationships are derived directly from microtomographic images. This is illustrated for a suite of four samples of Fontainebleau sandstone with porosities ranging from 7.5% to 22%. A finite‐element method is used to derive the elastic properties of digitized images. By estimating and minimizing several sources of numerical error, very accurate predictions of properties are derived in excellent agreement with experimental measurements over a wide range of the porosity. We consider the elastic properties of the digitized images under dry, water‐saturated, and oil‐saturated conditions. The observed change in the elastic properties due to fluid substitution is in excellent agreement with the exact Gassmann's equations. This shows both the accuracy and the feasibility of combining microtomographic images with elastic calculations to accurately predict petrophysical properties of individual rock morphologies. We compare the numerical predictions to various empirical, effective medium and rigorous approximations used to relate the elastic properties of rocks to porosity under different saturation conditions.

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Mechanisms by which waterflood residual oil is mobilized and recovered during tertiary gasflooding at quasistatic rates and strongly water-wet conditions were investigated with 2D glass micromodels. Two three-phase oil/water/gas systems were used in the displacement experiments. One system had a positive spreading coefficient, the other a negative coefficient. Results for the two systems were compared to determine the differences in displacement mechanisms and oil recovery efficiency. Displacement in both systems proceeds by a double-drainage mechanism where a gas/oil displacement is always associated with an oil/water displacement. The oil/water displacement leads to coalescence and reconnection of oil blobs. Oil recovery was significantly higher for the positive spreading system. The higher displacement efficiency resulted from flow through thin but continuous oil films that always separated the oil and water phases in the positive spreading system. The absence of oil films and the possibility of direct gas/water displacements reduced oil recovery for the negative spreading system.

A reservoir carbonate core plug has been imaged in 3D across a range of length scales using high resolution X-ray microtomography (µ-CT). Data from the original 40-mm diameter plug was obtained at the vug scale (42 µm resolution) and allows the size, shape and spatial distribution of the disconnected vuggy porosity, φ vug = 3.5% to be measured. Within the imaged volume over 32,000 separate vugs are identified and a broad vug size distribution is measured. Higher resolution images, down to 1.1 µm resolution, on subsets of the plug exhibit interconnected porosity and allow one to measure characteristic, intergranular pore size. Pore scale structure and petrophysical properties (permeability, drainage capillary pressure, formation factor, and NMR response) are derived directly on the highest resolution tomographic dataset. We show that data over a range of porosity can be computed from a single plug fragment. Data for the carbonate core is compared to results derived from 3D images of clastic cores and strong differences noted. Computations of permeability are compared to conventional laboratory measurements on the same core material with good agreement. This demonstrates the feasibility of combining digitized images with numerical calculations to predict properties and derive cross-correlations for carbonate lithologies.

We consider a family of statistical measures based on the Euler-Poincaré characteristic of n-dimensional space that are sensitive to the morphology of disordered structures. These measures embody information from every order of the correlation function but can be calculated simply by summing over local contributions. We compute the evolution of the measures with density for a range of disordered microstructural models; particle-based models, amorphous microstructures, and cellular and foamlike structures. Analytic results for the particle-based models are given and the computational algorithm verified. Computational results for the different microstructures exhibit a range of qualitative behavior. A length scale is derived based on two-point autocorrelation functions to allow qualitative comparison between the different structures. We compute the morphological parameters for the experimental microstructure of a sandstone sample and compare them to three common stochastic model systems for porous media. None of the statistical models are able to accurately reproduce the morphology of the sandstone.