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To address the high computational cost of particle tracking for realistic Eulerian–Lagrangian simulations, a novel efficient and robust particle tracking method (RT method) for unstructured meshes is presented. The method, for the first time, leverages both hardware ray tracing (RT) cores and GPU parallel computing technology to accelerate Eulerian–Lagrangian simulations. The method includes a hardware-accelerated hosting cell locator using bounding volume hierarchy tree (BVH) and a robust treatment of particle-wall interaction (multiple specular reflection) using an improved neighbor searching approach. The method is implemented in a GPU-accelerated open-source code, which is verified against a reference neighbor-searching particle-tracking method (NS method) and experimental observations. To evaluate the performance of our method, several numerical simulations of fluid-driven scalar transport problem are solved. Using a verification case, we show that the particle distribution simulated by our code is in a good agreement with an experimental observation. Tracking failures and stuck particles are not observed in any simulations. Benchmark results indicate that our RT method leads to a roughly 1.8 − 2.0 × performance improvement compared to the reference NS method for large-scale simulations (millions of mesh cells and particles).

This paper describes recent work on image-based network modeling of multiphase flow. The algorithm expands the range of flow scenarios and boundary conditions that can be implemented using dynamic network modeling, the most significant advance being the ability to model simultaneous injection of immiscible fluids under either transient or steady-state conditions using non-periodic domains. Pore-scale saturation distributions are solved rigorously from two-phase mass conservation equations simultaneously within each pore. Results show that simulations using a periodic network fail to track saturation history because periodic domains limit how the bulk saturation can evolve over time. In contrast, simulations using a non-periodic network with fractional flow as the boundary condition can account for behavior associated with both hysteresis and saturation history, and can capture phenomena such as the long pressure and saturation tails that are observed during dynamic drainage processes. Results include a sensitivity analysis of relative permeability to different model variables, which may provide insight into mechanisms for a variety of transient, viscous dominated flow processes.

Microtomography is an emerging technique for particle and particulate-materials characterization. To use this technology effectively, robust and accurate computational algorithms are needed to compute relevant particle properties, including particle surface area and particle-particle contact area. However, the most accurate algorithms that have been developed for computing the exposed (void/solid) surface area in a microtomography image cannot be used directly for computing surface areas or particle-particle contact areas for individual particles in a dense packing. This paper presents an algorithm for extracting particle contact areas from a digitized, segmented image of a packed granular material, which in turn can be used to find individual particle surface areas (even if the complete surfaces are not exposed because of contacts in the packing). Results show that small errors in the binary surface-area computations are magnified in the course of determining particle contact areas; the total error in the computation depends mainly on the size of the contact area in voxel units.

Fabrication of 2.5D rock-based micromodels with high resolution features is presented using SU-8 multi-layer lithography and nickel electroforming for nickel molds. Processes associated with SU-8 were carefully optimized by the use of the vacuum contact, the use of UV filter, and controls of UV exposure doses and baking times. The use of SU-8 MicroSpray enabled the easy fabrication of multi-layers of SU-8, while exhibiting some total thickness variations. The thirteen layered SU-8 samples showed reliable patterning results for features at 10 and 25 μm resolutions, and minor pattern distortions of features at the 5 μm resolution. Flycutting method employed in multi-layer lithography of SU-8 yielded accurate total thickness control within ±1.5 μm and excellent pattern formation for all of 5, 10, and 25 μm features. Electroforming of nickel was optimized with electroplating bath composition and electroplating parameters such as current density to realize the high resolution nickel mold. The fabricated nickel molds from flycutting based SU-8 samples revealed the feasibility of manufacturing the minimum features down to 5 μm for thirteen layers without any pattern distortions. The replication-based micromolding method will allow for fabrication of micromodels in a variety of materials such as polymers and ceramics. The high resolution, 2.5D micromodels will be used for investigation of pore-scale fluid transport, which will aid in understanding the complicated fluidic phenomena occurring in the 3D reservoir rock.Copyright © 2015 by ASME

A confocal Micro-Particle Image Velocimetry (C-μPIV) technique along with associated post image processing algorithms is established to quantify three dimensional distributions of nano-particle velocity and concentration at the micro-scale (pore-scale) in 2.5D porous media designed from a Boise rock sample. In addition, an in-situ, non-destructive method for measuring the geometry of the micro-model, including its depth, is described and demonstrated. The particle experiments use 900 nm fluorescence labeled polystyrene particles at a flow rate of 10 nLmin−1 and confocal laser scanning microscopy (CLSM), while in-situ geometry measurements use regular microscope along with Rhodamine dye and a depth-to-fluorescence-intensity calibration. Image post-processing techniques include elimination of background noise and signal from adsorbed nano-particle on the inner surfaces of the micro-model. In addition, a minimization of depth of focus technique demonstrates a capability of optically thin slice allowing us to measure depth wise velocity in 2.5D micro-model. The mean planar components of the particle velocity of the steady-state flow and particle concentration distributions were measured in three dimensions. Particle velocities range from 0.01 to 122 μm s−1 and concentrations from 2.18 × 103 to 1.79 × 104 particles mm−2. Depth-wise results show that mean velocity closer to the top wall is comparatively higher than bottom walls, because of higher planar porosity and smooth pathway for the nano-particles closer to the top wall. The three dimensional micro-model geometry reconstructed from the fluorescence data can be used to conduct numerical simulations of the flow in the as-tested micro-model for future comparisons to experimental results after incorporating particle transport and particle-wall interaction models.Copyright © 2015 by ASME

Traditional particle-characterization techniques require particles to be dispersed from their original form, which destroys important morphologic information in materials such as aggregates or porous materials. X-ray computed microtomography provides a powerful tool for non-destructive analysis. However, robust techniques for comprehensive material characterization of these images have not been developed. In this paper we present a new algorithm for the computer analysis of particulate materials from high-resolution tomography images. The key aspect of the algorithm is the assignment of every solid-phase voxel in the image to its associated particle in a physically representative manner, which is in essence a particle-scale computer reconstruction of the material. Once this digital reconstruction is obtained, a vast amount of morphologic information can be extracted, including parameters obtained by traditional particle-analysis techniques (e.g., particle-size distribution and porosity) as well as parameters not usually available (e.g., spatial correlations in particle size, particle aspect ratios, surface areas, and orientations, particle contacts, particle coordination numbers, and more). Additionally, the computer reconstruction allows for complex manipulations such as the comparison of a specific parameter for two different particle-size classes within the material. The paper includes validation of the algorithm using computer-generated packings, as well as an example using microtomography data from a real material.

The modeling of fluid transport in fibrous materials is important for many applications. Most models operate at the continuum level, which requires an a priori knowledge of spatially averaged transport parameters. Alternatively, highly detailed models, in which the momentum equations are solved directly, require major simplifying assumptions. Thus, it is desirable to use intermediate-level techniques that model transport using first principles, but that are appropriate for real engineering processes. In this work, pore-scale network modeling is adapted for fibrous materials and tested for a large range of fibrous structures and solid volume fractions. A novel technique is used to generate prototype network structures from Voronoi diagrams. The Voronoi networks are coupled with two different multiphase flow algorithms, enabling the modeling of various displacement processes relevant to engineering. Permeability predictions agree well with known values. Effects of dynamics, wettability, and material structure on displacement were studied. This modeling technique not only allows for better quantification of how microscale properties affect macroscopic transport, but helps reduce the number of experiments required to predict continuum transport parameters for various materials and processes.

A rock-based micromodel was designed using depth averaging with Boise rock digital images obtained from the X-ray micro-computed tomography. Design optimization of 2.5D micromodels was carried out using computational fluid dynamics (CFD) simulations through error analysis of dynamic flow parameters (velocities and permeability), which showed the close dynamic flow match between the actual 3D rock and the optimized 2.5D micromodel. Multiple numbers of polymer micromodels were microfabricated via micromilling of a brass mold insert and hot embossing in polymethylmethacrylate (PMMA). The design optimization and the replication-based microfabrication processes enabled the realistic pore geometry generation, which conforms to the pore dimensions of an actual rock sample but with coarser features in a polymer microfluidic platform. The microfabricated PMMA micromodel was used for fluidic characterization with nanoparticles to compare the flow patterns between the designed micromodel and the microfabricated micromodel. Particle motion paths observed in the particle experiments showed the consistent similarity of stream-traces from the CFD simulations of the designed 2.5D micromodel. Further fluidic investigation on the 2.5D rock-based micromodels will provide better understanding on fluid transport mechanism in porous media.Copyright © 2012 by ASME

Microfluidic polymethylmethacrylate (PMMA) devices for study of particle transport in artificial porous media were designed and microfabricated using hot embossing with a brass mold insert containing a microchannel network with eight layers. After thermal bonding to enclose the microchannel network, a process protocol was applied to successfully remove bubbles in the PMMA device. Characterization protocols were developed for study of fluorescent particle tracking, accumulation, and retention in these microfluidic chip artificial porous media. Particle accumulation and retention was observed throughout the microfluidic network domain and predominantly at the inlet section of the PMMA device due to entrance effects. Particle Image Velocimetry of the PMMA device allowed for generating velocity profiles in the chip microchannel networks.Copyright © 2011 by ASME

Summary X-ray computed microtomography (XMT) is used for high-resolution, nondestructive imaging and has been applied successfully to geologic media. Despite the potential of XMT to aid in formation evaluation, currently it is used mostly as a research tool. One factor preventing more widespread application of XMT technology is limited accessibility to microtomography beamlines. Another factor is that computational tools for quantitative image analysis have not kept pace with the imaging technology itself. In this paper, we present a new grain-based algorithm used for network generation. The algorithm differs from other approaches because it uses the granular structure of the material as a template for creating the pore network rather than operating on the voxel set directly. With this algorithm, several advantages emerge: the algorithm is significantly faster computationally, less dependent on image resolution, and the network structure is tied to the fundamental granular structure of the material. In this paper, we present extensive validation of the algorithm using computer-generated packings. These analyses provide guidance on issues such as accuracy and voxel resolution. The algorithm is applied to two sandstone samples taken from different facies of the Frontier Formation in Wyoming, USA, and imaged using synchrotron XMT. Morphologic and flow-modeling results are presented.

The entrapment of nonwetting phase fluids in unconsolidated porous media systems is strongly dependent on the pore-scale geometry and topology. Synchrotron X-ray tomography allows us to nondestructively obtain high-resolution (on the order of 1-10 micron), three-dimensional images of multiphase porous media systems. Over the past year, a number of multiphase porous media systems have been imaged using the synchrotron X-ray tomography station at the GeoSoilEnviroCARS beamline at the Advanced Photon Source. For each of these systems, we are able to: (1) obtain the physically-representative network structure of the void space including the pore body and throat distribution, coordination number, and aspect ratio; (2) characterize the individual nonwetting phase blobs/ganglia (e.g., volume, sphericity, orientation, surface area); and (3) correlate the porous media and fluid properties. The images, data, and network structure obtained from these experiments provide us with a better understanding of the processes and phenomena associated with the entrapment of nonwetting phase fluids. Results from these experiments will also be extremely useful for researchers interested in interphase mass transfer and those utilizing network models to study the flow of multiphase fluids in porous media systems.