Pore-scale simulation of gas displacement after water flooding using three-phase lattice Boltzmann method

Water flooding is a commonly used technique to improve oil recovery, although the amount of oil left in reservoirs after the procedure is still significant. Gas displacement after water flooding is an effective way to recover residual oil, but the occurrence state and flow principles of multiphase fluid after gas injection are still ambiguous. Therefore, the gas displacement process after water flooding should be studied on the pore scale to provide a basis for formulating a reasonable gas injection program. Most of the current pore-scale studies focus on two-phase flow, while simulations that account for the influence of oil-gas miscibility and injected water are seldom reported. In this work, the multi-component multi-phase Shan-Chen lattice Boltzmann model is used to simulate the gas displacement after water flooding in a porous medium, and the effects of injected water, viscosity ratio, pore structure, and miscibility are analyzed. It is established that the injected water will cause gas flow path variations and lead to premature gas channeling. Under the impact of capillary pressure, the water retained in the porous medium during the water flooding stage further imbibes into the tiny pores during gas injection and displaces the remaining oil. When miscibility is considered, the oil-gas interface disappears, eliminating the influence of the capillary effect on the fluid flow and enabling the recovery of remaining oil at the corner. This study sheds light on the gas displacement mechanisms after water flooding from the pore-scale perspective and provides a potential avenue for improving oil recovery.Document Type: Original articleCited as: Wang, S., Chen, L., Feng, Q., Chen, L., Fang, C., Cui, R. Pore-scale simulation of gas displacement after water flooding using three-phase lattice Boltzmann method. Capillarity, 2023, 6(2): 19-30. https://doi.org/10.46690/capi.2023.02.0

Prognostication of chronic disorders of consciousness using brain functional networks and clinical characteristics

Disorders of consciousness are a heterogeneous mixture of different diseases or injuries. Although some indicators and models have been proposed for prognostication, any single method when used alone carries a high risk of false prediction. This study aimed to develop a multidomain prognostic model that combines resting state functional MRI with three clinical characteristics to predict one year outcomes at the single-subject level. The model discriminated between patients who would later recover consciousness and those who would not with an accuracy of around 90% on three datasets from two medical centers. It was also able to identify the prognostic importance of different predictors, including brain functions and clinical characteristics. To our knowledge, this is the first implementation reported of a multidomain prognostic model based on resting state functional MRI and clinical characteristics in chronic disorders of consciousness. We therefore suggest that this novel prognostic model is accurate, robust, and interpretable.Comment: Although some prognostic indicators and models have been proposed for disorders of consciousness, each single method when used alone carries risks of false prediction. Song et al. report that a model combining resting state functional MRI with clinical characteristics provided accurate, robust, and interpretable prognostications. 52 pages, 1 table, 7 figure

Pore-network modeling of flow in shale nanopores: Network structure, flow principles, and computational algorithms

Hydrocarbons in subsurface nanoporous media, such as shale, are promising energy resources to compensate for the shortage of conventional reservoirs. Pore-network modeling serves as a valuable tool for simulating microscale fluid transport and elucidating flow physics in porous media. However, traditional pore-network models have failed to capture features of spatial structure and fluid flow in unconventional shale rock. This work presents a critical review of pore-network modeling of single-phase and two-phase flow in shale rock. Pore-network modeling advances of shale are reviewed based on three major parts: network morphology and geometries, flow principles in nanocapillaries, and pore-network computational algorithms. First, based on key geological features of shale rock, we analyze network topology, multiscale network, pore geometries, and network representativeness of shale pore-network models. Then, we discuss four important aspects that may influence flow principles of fluids in nanocapillaries: gas and liquid slippage, sorption and diffusion behavior, hydrocarbon thermodynamics, and the presence of water. Finally, we present pore-network modeling methods used for flow simulations in shale rock, including quasi-static and dynamic algorithms. We hope that this review could shed light on fundamentals of pore-network modeling of shale rock

Pore-network modeling of flow in shale nanopores: Network structure, flow principles, and computational algorithms

Hydrocarbons in subsurface nanoporous media, such as shale, are promising energy resources to compensate for the shortage of conventional reservoirs. Pore-network modeling serves as a valuable tool for simulating microscale fluid transport and elucidating flow physics in porous media. However, traditional pore-network models have failed to capture features of spatial structure and fluid flow in unconventional shale rock. This work presents a critical review of pore-network modeling of single-phase and two-phase flow in shale rock. Pore-network modeling advances of shale are reviewed based on three major parts: network morphology and geometries, flow principles in nanocapillaries, and pore-network computational algorithms. First, based on key geological features of shale rock, we analyze network topology, multiscale network, pore geometries, and network representativeness of shale pore-network models. Then, we discuss four important aspects that may influence flow principles of fluids in nanocapillaries: gas and liquid slippage, sorption and diffusion behavior, hydrocarbon thermodynamics, and the presence of water. Finally, we present pore-network modeling methods used for flow simulations in shale rock, including quasi-static and dynamic algorithms. We hope that this review could shed light on fundamentals of pore-network modeling of shale rock

Achieving High Performance Electrode for Energy Storage with Advanced Prussian Blue-Drived Nanocomposites—A Review

Recently, Prussian blue analogues (PBAs)-based anode materials (oxides, sulfides, selenides, phosphides, borides, and carbides) have been extensively investigated in the field of energy conversion and storage. This is due to PBAs’ unique properties, including high theoretical specific capacity, environmental friendly, and low cost. We thoroughly discussed the formation of PBAs in conjunction with other materials. The performance of composite materials improves the electrochemical performance of its energy storage materials. Furthermore, new insights are provided for the manufacture of low-cost, high-capacity, and long-life battery materials in order to solve the difficulties in different electrode materials, combined with advanced manufacturing technology and principles. Finally, PBAs and their composites’ future challenges and opportunities are discussed

Achieving High Performance Electrode for Energy Storage with Advanced Prussian Blue-Drived Nanocomposites—A Review

Recently, Prussian blue analogues (PBAs)-based anode materials (oxides, sulfides, selenides, phosphides, borides, and carbides) have been extensively investigated in the field of energy conversion and storage. This is due to PBAs’ unique properties, including high theoretical specific capacity, environmental friendly, and low cost. We thoroughly discussed the formation of PBAs in conjunction with other materials. The performance of composite materials improves the electrochemical performance of its energy storage materials. Furthermore, new insights are provided for the manufacture of low-cost, high-capacity, and long-life battery materials in order to solve the difficulties in different electrode materials, combined with advanced manufacturing technology and principles. Finally, PBAs and their composites’ future challenges and opportunities are discussed