Pore-scale mechanism of the waterflooding process contributes to enhanced oil recovery, which has been widely emphasized in the petroleum industry. In this paper, pore-scale waterflooding experiments are carried out on mixed-wetted natural sandstone and 3D printed sandstone using micro-computed tomography (μ-CT). The high-resolution images of oil/water distribution in different stages of waterflooding cycles are acquired. The classification of residual oil after waterflooding is conducted using the shape factor and Euler number, which represents the shape and spatial connectivity, respectively. The in situ contact angles are measured on the segmented images and the pore-scale wettability of these two samples is analyzed. Then, the effects of pore structure, micro-fracture and wettability on the distribution of the patterns of residual oil are analyzed. The results indicate that the types of isolated, cluster, network, and film (only for natural sample) are the main forms of residual oil patterns after the waterflooding process. The negative correlation between the shape factor and the Euler number of the typical oil blocks are presented. The effect of wettability and pore geometry on the morphology of the oil/water interface is quantitatively studied. The capillary pressure is the key factor for the formation of the residual oil blocks, the morphology of which is controlled by both wettability and pore geometry.
analogs of natural rocks have been used in laboratory tests concerning geomechanical and transport properties. Rock analogs manufactured by 3D printing can be used to manufacture batch of the samples with specified heterogeneity compared to natural rocks. Rock analogs were manufactured with silica sand (SS) and gypsum powder (GP) using binder jetting (BJ) as well as with coated silica beads (CSB) using selective laser curing (SLC). The uniaxial and triaxial compressive tests were conducted to investigate the strength and deformation characteristics of 3DP rocks that were quantitatively compared with natural rocks. CSB and SS specimens experienced tensile failure, while the GP specimen has shown shear failure and shear-expansion behavior. The microstructural characteristics (e.g. grain shape, pore type, and bonding form) of the SS specimen were similar to a natural sandstone (Berea sandstone reported in the literature) with a relatively loose texture. In addition, 3DP rocks were more permeable than Berea sandstone (permeability of SS, CSB, and Berea sandstone was 12580.5mD, 9840.5mD, and 3950mD, respectively). The effect of microscopic mechanical behavior on macroscopic strength and failure characteristics was investigated using scanning electronic microscopy (SEM). CSB and SS specimens could be suitable to simulate the transport behavior of the highly permeable sedimentary rocks. The GP specimen could be used to study the large deformation characteristics and creep failure mode of highly stressed soft rocks. Despite the early stage of 3DP rock analog studies, the potential applications could be expanded by controlling the physical properties (e.g. wettability and surface roughness).
Varieties of pore‐scale numerical and empirical approaches have been proposed to predict the rock permeability when the pore structure is known, for example, microscopic computerized tomography (micro‐CT) technology. A comparative study on these approaches is conducted in this paper. A reference dataset of nine micro‐CT images of porous rocks is generated and processed including artificial sandpacks, tight sandstone, and carbonate. Multiple numerical and empirical approaches are used to compute the absolute permeability of micro‐CT images including the image voxel‐based solver (VBS), pore network model (PNM), Lattice Boltzmann method (LBM), Kozeny‐Carman (K‐C) equation, and Thomeer relation. Computational accuracy and efficiency of different numerical approaches are investigated. The results indicate that good agreements among numerical solvers are achieved for the sample with a homogeneous structure, while the disagreement increases with an increase in heterogeneity and complexity of pore structure. The LBM and VBS solver both have a relative higher computation accuracy, whereas the PNM solver is less accurate due to simplification on the topological structure. The computation efficiency of the different solver is generally computation resources dependent, and the PNM solver is the fastest, followed by VBS and LBM solver. As expected, empirical relation can over‐estimate permeability by a magnification of 50 or more, particularly for those strong heterogeneous structures reported in this study. Nevertheless, empirical relation is still applicable for artificial rocks.
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