Modeling of two-phase flow in heterogeneous wet porous media

The characterization of two-phase flow has been commonly based on homogeneous wet capillary models, which are limited to heterogeneous wet porous media. In this work, capillary pressure and relative permeability models for three heterogeneous wet systems are derived, which enable the analysis of the effect of oil-wet ratio on the two-phase flow mechanism. The capillary pressures, relative permeabilities and water cut curves of three systems are simulated at the primary drainage stage. The results show that water-wet and oil-wet systems exhibit drainage and imbibition characteristics, respectively, while heterogeneous wet systems show both of these characteristics, and a large oil- wet ratio is favourable to oil imbibition. Mixed-wet large and mixed-wet small systems have water-wet and oil-wet characteristics, respectively, at the end and the beginning of oil displacement. At the drainage stage, the oil-wet ratio can significantly decrease oil conductivity, while water conductivity is enhanced. The conductivity difference between oil and water firstly decreases and then increases with rising water saturation, and the difference diminishes with the increase in oil-wet ratio. The oil-wet ratio can reduce water displacement efficiency, and its effects on the water cut curves vary between the three systems due to wettability distribution and pore-size mutation. The mixed-wet small system has the strongest oil imbibition ability caused by the largest capillary pressure in oil-wet pores and the smallest drainage pressure in water-wet pores, and high water conductivity causes the greatest water cut. The trend of variations in the mixed-wet large system is opposite to that in the mixed-wet small system, and the fractional-wet system is located between the other two systems.Cited as: Xiao, Y., He, Y., Zheng, J., Zhao, J. Modeling of two-phase flow in heterogeneous wet porous media. Capillarity, 2022, 5(3): 41-50. https://doi.org/10.46690/capi.2022.03.0

Prediction of permeability of tight sandstones from mercury injection capillary pressure tests assisted by a machine-learning approach

Mercury injection capillary pressure analysis is a methodology for determining different petrophysical properties, including bulk density, porosity, and pore throat distribution. In this work, distinct parameters derived from mercury injection capillary pressure tests was considered for the prediction of permeability by coupling machine learning and theoretical approaches in a dataset composed of 246 tight sandstone samples. After quality checking the dataset, the feature selection was carried out by correlation analysis of different theoretical permeability models and statistical parameters with the measured permeability. Finally, porosity, median capillary pressure, Winland model, and mean pore-throat radius (corresponding to the saturation range 0.4-0.8) were chosen as the input features of the machine learning model. As the machine learning approach, a support vector machine (SVM) model with a radial basis function kernel was proposed. Furthermore, the model and its metaparameters were trained with a particle swarm optimization (PSO) algorithm to avoid over-fitting or under-fitting. In contradiction to the theoretical models, the implemented SVM-PSO model could acceptably predict the experimentally measured permeability values with an R2 rate of over 0.88 for training and testing datasets. The introduced approach could reduce the mean relative errors from about 10 to values less than 0.45. The improvements were more significant for low permeability samples. This successful implementation shows the potential of coupled usage of theoretical and machine learning methodologies for improved prediction of permeability of tight sandstone rocks.Cited as: Abbasi, J., Zhao, J., Ahmed, S., Jiao, L., Andersen, P., Cai, J. Prediction of permeability of tight sandstones from mercury injection capillary pressure tests assisted by a machine-learning approach. Capillarity, 2022, 5(5): 91-104. https://doi.org/10.46690/capi.2022.05.0

Fractal Analysis of Microscale and Nanoscale Pore Structures in Carbonates Using High-Pressure Mercury Intrusion

This paper investigated fractal characteristics of microscale and nanoscale pore structures in carbonates using High-Pressure Mercury Intrusion (HPMI). Firstly, four different fractal models, i.e., 2D capillary tube model, 3D capillary tube model, geometry model, and thermodynamic model, were used to calculate fractal dimensions of carbonate core samples from HPMI curves. Afterwards, the relationships between the calculated fractal dimensions and carbonate petrophysical properties were analysed. Finally, fractal permeability model was used to predict carbonate permeability and then compared with Winland permeability model. The research results demonstrate that the calculated fractal dimensions strongly depend on the fractal models used. Compared with the other three fractal models, 3D capillary tube model can effectively reflect the fractal characteristics of carbonate microscale and nanoscale pores. Fractal dimensions of microscale pores positively correlate with fractal dimensions of the entire carbonate pores, yet negatively correlate with fractal dimensions of nanoscale pores. Although nanoscale pores widely develop in carbonates, microscale pores have greater impact on the fractal characteristics of the entire pores. Fractal permeability model is applicable in predicting carbonate permeability, and compared with the Winland permeability model, its calculation errors are acceptable

Influence of light and temperature on the development and denitrification potential of periphytic biofilms

Periphytic biofilms are microbial aggregates commonly present in submerged aquatic environments and play a significant role in nutrient cycling. In recent years, utilization of natural periphytic biofilms in wastewater treatment and water restoration attracts growing research interests. Light and temperature are two important environmental factors known to affect the development of periphytic biofilms and can be manipulated for the regulation of the biofilm properties. In this work, effects of light and temperature on the development and function (denitrification potential) of periphytic biofilms were investigated using a microcosm experiment. Results showed that thicker periphytic biofilms with higher Chlorophyll a, extracellular polymeric substances (EPS), and total phosphorus contents were developed under higher temperature. Whereas, biomass accumulation was more rapid for periphytic biofilms under higher irradiance. The denitrification potential rate was negatively associated with irradiance, which can be linked to the influence of irradiance on biofilm structure and microbial composition. A relatively lower irradiance is recommended when using periphytic biofilms in nitrogen removal from wastewater. (C) 2017 Elsevier B.V. All rights reserved.</p

SIRT1 Promotes Osteogenic Differentiation in Human Dental Pulp Stem Cells through Counteracting the Activation of STAT3

Human dental pulp stem cells (hDPSCs), which are characterized by self-renewal capacity and the ability of multilineage differentiation, have gained increased attention in regenerative medicine recently. Histone acetylation modulator proteins (HAMPs) are a protein family that mediates the modification and identification of histone acetylation and participates in various critical cellular processes. Here, we comprehensively surveyed the expression profile of HAMPs during osteoblast differentiation of hDPSCs and found that the HDAC class III pathway was upregulated, whereas the signal transducer and activator of transcription 3 (STAT3) signaling was downregulated during osteogenesis. Further laboratory research demonstrated that Sirtuin-1 (SIRT1), a class III HDAC, was upregulated and STAT3 activation was downregulated during osteogenic differentiation. SIRT1 counteracted the activation of STAT3 to promote osteogenic differentiation of hDPSCs at 7 and 21 days in both Western blot assay and chemical staining, which highlights the promising utility of SIRT1 activators in hDPSCs-based therapies for bone augmentation strategies and provides clinical insights that may lead to the development of osteogenic agents