Pore-scale characteristics of multiphase flow in heterogeneous porous media using the lattice Boltzmann method

Impact of Wettability on CO2 Dynamic Dissolution in Three-Dimensional Porous Media: Pore-Scale Simulation Using the Lattice Boltzmann Method

Understanding the dissolution behavior of supercritical CO2 (scCO2) in porous media is crucial for efficient CO2 storage. However, the precise modeling of dynamic dissolution behavior at this pore scale remains a huge challenge, and the impact of wettability on this process still needs to be clarified. In this study, the influence of rock wettability on CO2 dynamic dissolution in the three-dimensional porous media is investigated using the lattice Boltzmann method (LBM). The LBM is coupled with scCO2-water two-phase flow, solute transport, and heterogeneous and homogeneous reactions. The size, number, and dissolution pattern of scCO2 bubbles during the dissolution process are observed under strongly water-wet, weakly water-wet, intermediate-wet, and mixed-wet conditions. The CO2(aq) concentration and pH are investigated, followed by a quantitative investigation of the impact of wettability on the specific interface area and the mass transfer coefficient. An empirical relationship between the specific interface area and scCO2 saturation is established. The findings reveal that under weakly water-wet and intermediate-wet conditions, the sizes of scCO2 clusters and monomers are small and mostly distributed at the dead end of the pores. In contrast, under strongly water-wet and mixed-wet conditions, the clusters are larger and interconnected, and distributed in the center of the pore. This results in a greater scCO2-water interface area, consequently enhancing the dissolution rate. Furthermore, a strong linear correlation is observed between scCO2 saturation and specific interface area. It is noted that as the hydrophilicity of the rock increases, the mass transfer coefficient initially rises and then declines.

Effects of grain size and small-scale bedform architecture on CO2 saturation from buoyancy-driven flow

Small-scale (mm-dm scale) heterogeneity has been shown to significantly impact CO₂ migration and trapping. To investigate how and why different aspects of small-scale heterogeneity affect the amount of capillary trapping during buoyancy-driven upward migration of CO₂, we conducted modified invasion percolation simulations on heterogeneous domains. Realistic simulation domains are constructed by varying two important aspects of small-scale geologic heterogeneity: sedimentary bedform architecture and grain size contrast between the matrix and the laminae facies. Buoyancy-driven flow simulation runs cover 59 bedform architecture and 40 grain size contrast cases. Simulation results show that the domain effective CO₂ saturation is strongly affected by both grain size and bedform architecture. At high grain size contrasts, bedforms with continuous ripple lamination at the cm scale tend to retain higher CO₂ saturation than bedforms with discontinuous or cross lamination. In addition, the "extremely well sorted" grain sorting cases tend to have lower CO₂ saturation than expected for cross-laminated domains. Finally, both a denser CO₂ phase and greater interfacial tension increase CO₂ saturation. Again, variation in fluid properties seems to have a greater effect on CO₂ saturation for cross-laminated domains. This result suggests that differences in bedform architecture can impact how CO₂ saturation values respond to other variables such as grain sorting and fluid properties.

Experimental and computational advances on the study of Viscous Fingering: An umbrella review

During the production of heavy oil reservoirs, the movement of the fluids, namely oil and water, significantly affects the production rates. This movement is influenced by the mobility ratio and directly affects variables such as The Water-Oil-Ratio (WOR), production costs, and recovery factor (RF). Moreover, Viscous Fingering, a phenomenon that describes the fluid movement through porous media, has been identified as the root cause of high-water production rates. Studying and comprehending this phenomenon is necessary to understand Oil & Gas companies' challenges nowadays to produce heavy oil. For example, this phenomenon has a direct impact on the assets managed by Enhanced Oil Recovery Techniques (EOR) that involves the injection of fluids such as polymer, water, and CO₂ flooding, SAGD, VAPEX, CSP and ECSP, among others. Due to its importance, this paper review and highlights the main computational and experimental studies for over more than 30 years (from the late 1980s) about Viscous Fingering, especially in the oil industry. Also, the need for further studies involving the newest experimental and computational technologies and new novel methodologies for the comprehension of Viscous Fingering is discussed. This review aims to give an overview of the technological developments in the study of Viscous Fingering, not only to understand it but also to illustrate how scientists have been developing new technologies to overcome the consequences caused by this phenomenon.

Predicting porosity, permeability, and tortuosity of porous media from images by deep learning

Convolutional neural networks (CNN) are utilized to encode the relation between initial configurations of obstacles and three fundamental quantities in porous media: porosity ([Formula: see text]), permeability (k), and tortuosity (T). The two-dimensional systems with obstacles are considered. The fluid flow through a porous medium is simulated with the lattice Boltzmann method. The analysis has been performed for the systems with [Formula: see text] which covers five orders of magnitude a span for permeability [Formula: see text] and tortuosity [Formula: see text]. It is shown that the CNNs can be used to predict the porosity, permeability, and tortuosity with good accuracy. With the usage of the CNN models, the relation between T and [Formula: see text] has been obtained and compared with the empirical estimate.

Velocity dependent up-winding scheme for node control volume finite element method for fluid flow in porous media

We present a novel velocity based up-winding scheme for the node control volume finite element (NCVFE) method. The NCVFE method solves for the pressure at the vertices of elements and a control volume mesh is constructed around them; where the advection of fluids is modelled. Therefore, each element shares several control volumes, and traditionally the fluid saturations used in calculating the mobilities over each element  −  hence updating pressure  −  are arithmetically weighted. In this paper, we use the velocity vector to allocate the upstream direction of the fluid flow in each element and use the upstream fluid saturation in calculating the mobility needed for the pressure equation. We test his novel approach using triangle and tetrahedron elements, and we show that it produces more accurate fluid saturation profiles than the traditional approach. The method can easily be implemented in current NCVFE simulators.

Lattice Boltzmann-Discrete Element Modeling Simulation of SCC Flowing Process for Rock-Filled Concrete

Since invented in 2003, rock-filled concrete (RFC) has gained much attention and has been successfully applied in more and more civil and hydraulic projects in China. This study developed a numerical framework to simulate self-compacting concrete (SCC) flows in the voids among rocks of RFC, which couples the lattice Boltzmann method and discrete element method (DEM). The multiple-relaxation-time scheme is used to simulate self-compacting mortar (SCM) for better stability while the motion of coarse aggregates in SCC is simulated with DEM. The immersed moving boundary method is incorporated to deal with the interactions between coarse aggregates and SCM. After validation, the coupled framework is applied to study SCC flows in a single channel and in porous media with multi-channels. A passing factor PF was proposed and calculated to describe quantitatively the passing ability of SCC through a single channel. The study found that jamming of SCC occurs when the ratio Ar of the gap width to particle diameter is smaller than 2.0 and the jamming risk increases with solid particles fraction while the passing ability has a weak relation with the pressure gradient. Further, SCC flow is self-tuning in porous media with multi-channels and it is prone to go through larger or wider gaps. Exceeded existence of narrow gaps will significantly increase the jamming risk.