[1] Nondestructive imaging methods such as X-ray computed tomography (CT) yield high-resolution, three-dimensional representations of pore space and fluid distribution within porous materials. Steadily increasing computational capabilities and easier access to X-ray CT facilities have contributed to a recent surge in microporous media research with objectives ranging from theoretical aspects of fluid and interfacial dynamics at the pore scale to practical applications such as dense nonaqueous phase liquid transport and dissolution. In recent years, significant efforts and resources have been devoted to improve CT technology, microscale analysis, and fluid dynamics simulations. However, the development of adequate image segmentation methods for conversion of gray scale CT volumes into a discrete form that permits quantitative characterization of pore space features and subsequent modeling of liquid distribution and flow processes seems to lag. In this paper we investigated the applicability of various thresholding and locally adaptive segmentation techniques for industrial and synchrotron X-ray CT images of natural and artificial porous media. A comparison between directly measured and image-derived porosities clearly demonstrates that the application of different segmentation methods as well as associated operator biases yield vastly differing results. This illustrates the importance of the segmentation step for quantitative pore space analysis and fluid dynamics modeling. Only a few of the tested methods showed promise for both industrial and synchrotron tomography. Utilization of local image information such as spatial correlation as well as the application of locally adaptive techniques yielded significantly better results.Citation: Iassonov, P., T. Gebrenegus, and M. Tuller (2009), Segmentation of X-ray computed tomography images of porous materials: A crucial step for characterization and quantitative analysis of pore structures, Water Resour. Res., 45, W09415,
Elastic waves have been observed to increase productivity of oil wells, although the reason for the vibratory mobilization of the residual organic fluids has remained unclear. Residual oil is entrapped as ganglia in pore constrictions because of resisting capillary forces. An external pressure gradient exceeding an “unplugging” threshold is needed to carry the ganglia through. The vibrations help overcome this resistance by adding an oscillatory inertial forcing to the external gradient; when the vibratory forcing acts along the gradient and the threshold is exceeded, instant “unplugging” occurs. The mobilization effect is proportional to the amplitude and inversely proportional to the frequency of vibrations. We observe this dependence in a laboratory experiment, in which residual saturation is created in a glass micromodel, and mobilization of the dyed organic ganglia is monitored using digital photography. We also directly demonstrate the release of an entrapped ganglion by vibrations in a computational fluid‐dynamics simulation.
Nondestructive imaging methods such as x‐ray computed tomography (CT) yield high‐resolution, grayscale, three‐dimensional visualizations of pore structures and fluid interfaces in porous media. To separate solid and fluid phases for quantitative analysis and fluid dynamics modeling, segmentation is applied to convert grayscale CT volumes to discrete representations of media pore space. Unfortunately, x‐ray CT is not free of artifacts, which complicates segmentation and quantitative image analysis due to obscuration of significant features or misinterpretation of attenuation values of a single material in different image sections. Images or volumes emanating from polychromatic (industrial) scanners are especially prone to high noise levels, beam hardening, scattered x‐rays, or ring artifacts. These problems can be alleviated to a certain extent through application of metal filters, careful detector calibration, and sample centering, but they cannot be completely avoided. We have developed a simple three‐dimensional approach to numerically correct for image artifacts using sequential segmentation. This procedure leads to a significant improvement of grayscale data as well as final segmentation results with reasonable computational demand.
[1] Numerous observations and laboratory experiments suggest that elastic vibrations can significantly enhance transport of nonaqueous phase liquids (NAPLs) in porous media. Our analyses suggest that in the low-frequency range, capillary forces and nonlinear rheology of the fluid may be predominant mechanisms of vibratory stimulation. Consequently, a model of these mechanisms is built to explain the effect of sonic waves on fluid percolation. The model shows that the low-frequency elastic waves of relatively low intensity can significantly enhance the flow rate of a yield stress fluid under small external pressure gradients and aid in the mobilization of entrapped NAPL blobs by reducing the value of the threshold gradient needed to displace the fluid. We estimate the intensity of a sonic field to be used in the possible field implementation of this method to be in the range of 0.2-125 W/m 2 .
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.