Digital material laboratory: Wave propagation effects in open-cell aluminium foams

This paper is concerned with numerical wave propagation effects in highly porous media using digitized images of aluminum foam -- Starting point is a virtual material laboratory approach -- The Aluminum foam microstructure is imaged by 3D X-ray tomography -- Effective velocities for the fluid-saturated media are derived by dynamic wave propagation simulations -- We apply a displacement-stress rotated staggered fnite-difference grid technique to solve the elastodynamic wave equation -- The used setup is similar to laboratory ultrasound measurements and the computed results are in agreement with our experimental data -- Theoretical investigations allow to quantify the influence of the interaction of foam and fluid during wave propagation – Together with simulations using an artificial dense foam we are able to determine the tortuosity of aluminum foa

Numerical estimation of carbonate properties using a digital rock physics workflow

Digital rock physics combines modern imaging with advanced numerical simulations to analyze the physical properties of rocks. In this paper we suggest a special segmentation procedure which is applied to a carbonate rock from Switzerland. Starting point is a CT-scan of a specimen of Hauptmuschelkalk. The first step applied to the raw image data is a non-local mean filter. We then apply different thresholds to identify pores and solid phases. Because we are aware of a non-neglectable amount of unresolved microporosity we also define intermediate phases. Based on this segmentation determine porosity-dependent values for the p-wave velocity and for the permeability. The porosity measured in the laboratory is then used to compare our numerical data with experimental data. We observe a good agreement. Future work includes an analytic validation to the numerical results of the p-wave velocity upper bound, employing different filters for the image segmentation and using data with higher resolution

Rock compressibility from microcomputed tomography images: Controls on digital rock simulations

Rock compressibility is a major control of reservoir compaction, yet only limited core measurements are available to constrain estimates. Improved analytical and computational estimates of rock compressibility of reservoir rock can improve forecasts of reservoir production performance and the geomechanical integrity of compacting reservoirs. The fast-evolving digital rock technology can potentially overcome the need for simplification of pores (e. g., ellipsoids) to estimate rock compressibility as the computations are performed on an actual pore-scale image acquired using 3D microcomputed tomography (micro-CT). However, the computed compressibility using a digital image is impacted by numerous factors, including imaging conditions, image segmentation, constituent properties, choice of numerical simulator, rock field of view, how well the grain contacts are resolved in an image, and the treatment of grain-to-grain contacts. We have analyzed these factors and quantify their relative contribution to the rock moduli computed using micro-CT images of six rocks: a Fontainebleau sandstone sample, two Berea sandstone samples, a Castelgate sandstone sample, a grain pack, and a reservoir rock. We find that image-computed rock moduli are considerably stiffer than those inferred using laboratory-measured ultrasonic velocities. This disagreement cannot be solely explained by any one of the many controls when considered in isolation, but it can be ranked by their relative contribution to the overall rock compressibility. Among these factors, the image resolution generally has the largest impact on the quality of image-derived compressibility. For elasticity simulations, the quality of an image resolution is controlled by the ratio of the contact length and image voxel size. Images of poor resolution overestimate contact lengths, resulting in stiffer simulation results