Pore Permeability Research Articles

Strength, Permeability and Multiscale Pore Characteristics of Cement-Based Materials with High-Volume Fly Ash Contents and Different Water-Binder Ratios

Strength, Permeability and Multiscale Pore Characteristics of Cement-Based Materials with High-Volume Fly Ash Contents and Different Water-Binder Ratios

Utilizing machine learning for flow zone indicators prediction and hydraulic flow unit classification

Reservoir characterization, essential for understanding subsurface heterogeneity, often faces challenges due to scale-dependent variations. This study addresses this issue by utilizing hydraulic flow unit (HFU) zonation to group rocks with similar petrophysical and flow characteristics. Flow Zone Indicator (FZI), a crucial measure derived from pore throat size, permeability, and porosity, serves as a key parameter, but its determination is time-consuming and expensive. The objective is to employ supervised and unsupervised machine learning to predict FZI and classify the reservoir into distinct HFUs. Unsupervised learning using K-means clustering and supervised algorithms including Random Forest (RF), Extreme Gradient Boosting (XGB), Support Vector Machines (SVM), and Artificial Neural Networks (ANN) were employed. FZI values from RCAL data formed the basis for model training and testing, then the developed models were used to predict FZI in unsampled locations. A methodical approach involves 3 k-fold cross-validation and hyper-parameter tuning, utilizing the random search cross-validation technique over 50 iterations was applied to optimize each model. The four applied algorithms indicate high performance with coefficients determination (R2) of 0.89 and 0.91 in training and testing datasets, respectively. RF showed the heist performance with training and testing R2 values of 0.957 and 0.908, respectively. Elbow analysis guided the successful clustering of 212 data points into 10 HFUs using k-means clustering and Gaussian mixture techniques. The high-quality reservoir zone was successfully unlocked using the unsupervised technique. It has been discovered that the areas between 2370–2380 feet and 2463–2466 feet are predicted to be high-quality reservoir potential areas, with average FZI values of 500 and 800, consecutively. The application of machine learning in reservoir characterization is deemed highly valuable, offering rapid, cost-effective, and precise results, revolutionizing decision-making in field development compared to conventional methods.

Dissemination of antibiotic resistance genes is regulated by iron oxides: Insight into the influence on bacterial transformation

The transportation of antibiotic resistance genes (ARGs) in manure-soil-plant continuums poses risks to human health. Horizontal gene transfer, particularly for bacterial transformation, is an important way for ARG dissemination. As crucial components in soils, iron oxides impacted the fates of various abiotic and biotic contaminants due to their active properties. However, whether they can influence the transformation of ARGs is unknown, which waits to be figured out to boost the assessment and control of ARG spread risks. In this study, we have investigated the effects of goethite, hematite, and magnetite (0–250 mg/L, with sizes < 100 nm and > 100 nm) on the transfer of ampicillin resistance genes to Escherichia coli cells. At lower iron oxide concentrations, the transformation of ARGs was first facilitated (transformation frequency reached up to 3.38-fold higher), but the facilitating effects gradually weakened and eventually disappeared as concentrations further increased. Particle size and iron oxide type were not the universal determinants controlling the transformation. At lower concentrations, iron oxides interacted with proteins and phospholipids in E. coli envelope structures, and induced the overgeneration of intracellular reactive oxygen species. Consequently, they led to pore formation and permeability enhancement on the cell membrane, thus promoting the transformation. The facilitation was also associated with the carrier-like effect of iron oxides for antibiotic resistance plasmids. At higher concentrations, the weakened facilitations were attributed to the aggregation of iron oxides. In this study, we highlight the crucial roles of the concentrations (contents) of iron oxides on the dissemination of ARGs in soils; this study may serve as a reference for ARG pollution control in future agricultural production.

Physico-chemical characterization of the tumour microenvironment of pancreatic ductal adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive lethal malignancy that accounts for more than 90% of pancreatic cancer diagnoses. Our research is focused on the physico-chemical properties of the tumour microenvironment (TME), including its tumoural extracellular matrix (tECM), as they may have an important impact on the success of cancer therapies. PDAC xenografts and their decellularized tECM offer a great material source for research in terms of biomimicry with the original human tumour. Our aim was to evaluate and quantify the physico-chemical properties of the PDAC TME. Both cellularized (native TME) and decellularized (tECM) patient-derived PDAC xenografts were analyzed. A factorial design of experiments identified an optimal combination of factors for effective xenograft decellularization. Our results provide a complete advance in our understanding of the PDAC TME and its corresponding stroma, showing that it presents an interconnected porous architecture with very low permeability and small pores due to the contractility of the cellular components. This fact provides a potential therapeutic strategy based on the therapeutic agent size.

Study on Main Factors Controlling Development Performance of Heterogeneous Composite Flooding in Post-Polymer Flooding Reservoir

Heterogeneous composite flooding has performed well with regard to enhanced oil recovery after polymer flooding in recent years. In order to significantly increase oil recovery, the development parameters should be designed differently for each well. However, it is difficult to rapidly allocate development parameters through the lowering of computational costs. Therefore, the authors of this paper carried out research to clarify the main controlling factors of parameter allocation. Firstly, the numerical simulation domain was separated into several regions, with injection wells and production wells at the center of each region. The statistical parameters of each region were calculated. Then, the water injection rate, liquid production rate, and chemical agent concentration were allocated based on the proportion of statistical parameters in each region. A large number of development schemes were designed by combining different injection and production allocations that were calculated based on each statistical parameter. Finally, the development performance of each scheme was simulated and analyzed. The statistical parameters corresponding to the best performance scheme were regarded as the main controlling factors of heterogeneous composite flooding after polymer flooding. These results showed that the main controlling factors for the allocation of the water injection rate were pore volume and permeability variation coefficient. The main controlling factors for liquid production rate were the remaining oil saturation, formation coefficient, and reservoir pressure. The main controlling factors for chemical agent concentration were pressure and permeability variation coefficient. These findings concerning the main factors controlling development parameter allocation were validated by practical application in several well groups of an actual reservoir model. This study provides references for improving heterogeneous composite flooding performance for post-polymer flooding reservoirs in the future.

Circular production of recycled binder from fly ash-based geopolymer concrete

This paper presents an investigation into the potential of recycling fly ash - based geopolymer concrete, to produce a recycled binder for circular re – use as starting material. The aforementioned would be a significant advantage over Portland cement which is non – recyclable, owing to its irreversible hydration. The experiment conducted involved crushing and sieving old parent fly ash – based geopolymer concrete, to separate out the paste from aggregate. The paste was then pulverized using a ball – mill to produce the recycled aluminosilicate starting material, herein referred to as recycled geopolymer cement (RGPC). Fly ash was blended with 0 to 100% RGPC, then used to prepare fresh geopolymer paste and mortar mixtures activated using a binary alkali activator consisting of sodium hydroxide and sodium silicate. Samples were cast then cured at 23 or 80 °C. The various tests done were workability, setting time, compressive strength, splitting tensile strength, drying shrinkage, water absorption, and volume of permeable pores. Analytical studies were done using X – ray diffraction, scanning electron microscopy and Fourier – transform infrared spectroscopy. Results showed that incorporation of RGPC into geopolymer mixtures generally led to reduction of workability and setting time, reduction of compressive and tensile strength, along with increase in drying shrinkage. It was, however, found that up to 60% RGPC can be incorporated into geopolymer mixtures while maintaining adequate performance suitable for structural applications. Unlike Portland cement, hardened geopolymer concrete is evidently recyclable to produce a circularly re – usable binder.

3D pore structure characterization and permeability anisotropy visualization simulation of fusain

The Jurassic‒Cretaceous coal seams in northern China are rich in fusains, and the pore size of the residual plant tissue in fusains is much larger than the limit value of seepage pores and even larger than that of some microfractures in coal. Therefore, understanding the 3D pore structure and permeability of fusains is helpful for determining the physical characteristics of inertinite-rich coal reservoirs. The porosity of the fusain varies widely, the pore structure has obvious directivity, and this study summarizes three pore types. Based on the visual distribution module of fluid migration, three types of seepage models of fusains were established, including the tubular cell structure seepage model, the broken cell wall pore seepage model, and the complete cell structure surface barrier seepage model. The results of the physical simulation verify the rationality of the three seepage models and show that the degree of fusification and cell pore fragmentation strongly affect the permeability of the fusain. For a low-rank coal reservoir with a rich fusain, the overall pore permeability is high, which is conducive to the seepage production of coalbed methane and is an important reference value for high-permeability layer selection.

Mechanical properties and gas permeability of silica-gel modified hydratable magnesium carboxylate bonded refractory castables in drying process

The hydratable magnesium carboxylate (HMC) bonded castables have a high-level gas permeability while the mechanical strength decreased sharply during drying process. Silica-gel with high activity is a porous structure after drying and can potentially increase the intermediate-temperature strength without reducing the gas permeability of the castables. In this study, the mechanism of silica-gel modified the HMC, and the effects on the properties of the castables were investigated. The surface of the hydration products of HMC is covered with a thin protective layer of siloxane network. The proportion of fine permeable pores (0.1 μm ∼1 μm) increased, optimizing the connected network channels in the castables. Compared to the pure HMC bonded castables, with the HMC/silica-gel mass ratio of 2, the cold modulus of rupture of the castables increased by 2 times after heat treatment in the range of 400 °C ∼600 °C. Especially, the permeability constants Darcian k1 and non-Darcian k2 increased by 37 times and 38 times after heat treatment at 600 °C, respectively.

Thermochemical energy storage performances of Co3O4-based honeycombs with multi-scale composite pores

Metal oxide redox system characterized open-loop operation, high energy density, and high reversibility, which is one of the most promising thermochemical energy storage technologies for the next-generation concentrated solar power plants. Most of the previous studies focused on the material properties, while the energy storage performance of oxide monolithic bodies, such as energy storage density and heat storage/release rate, has rarely been reported. In this paper, a novel and effective method for the improvement of the energy storage performance of oxide honeycombs with multi-scale composite pores is proposed and presented. Methyl cellulose and four common biomass materials, including bagasse, loofah, juniper leaf, and pine needle, were used as pore-forming agents for oxide honeycombs. The pyrolysis of methyl cellulose forms small-scale pores in the honeycomb bodies and contributes the major pore volume. The biomass templates further optimize the pore characteristics, all biomass-templated Co3O4-based honeycomb bodies have higher total pore volume and permeability than that of biomass-free honeycomb body. The honeycomb with 2.5 wt% pine needle achieves the highest energy storage density, with an average of 694.62 kJ/kg during the second to fifteenth cycles. In addition, the honeycomb containing 7.5 wt% pine needle has the highest energy store/release rate. Biomass-templated Co3O4-based honeycomb shows a high crushing strength, and there are no obvious cracks and structural deformations on its surface after 15 thermal cycles. The findings demonstrate that the methyl cellulose and biomass template method can effectively optimize the pore structure and energy storage properties of the oxide honeycombs, thereby expanding the application prospects of Co3O4-based honeycombs in thermochemical energy storage.

Synergic effect of metal-organic frameworks and process parameters on the properties of concrete subjected to accelerated carbonation

This study aims to develop a novel concrete that integrates a metal-organic frameworks (MOF) and accelerated carbonation curing to offset the emissions attributed to cement production. A MOF, NH2-MIL-125(Ti), was synthesized to sequester CO2 in concrete through accelerated carbonation curing. Its impact on the concrete properties was assessed while examining various process parameters, including MOF content, initial curing duration, carbonation curing duration, and carbonation curing pressure. The parameters were evaluated through CO2 uptake, phenolphthalein indicator solution, compressive strength, water absorption, and volume of permeable voids. The microstructure of carbonated MOF-incorporating concrete was characterized using powder X-ray diffraction analysis, scanning electron microscopy, and Fourier transform infrared spectroscopy. Experimental results showed that the addition of MOF promoted a higher degree of carbonation of cement, especially with a longer initial curing duration and higher pressure. Incorporating up to 6% MOF, by cement mass, in concrete cured for 20 h in open air, followed by 20 h of carbonation curing at a pressure of 1 bar, led to a CO2 uptake of 19%, carbonation depth of 11 mm, and 28-day strength of 46 MPa, water absorption of 4%, and permeable pore voids volume of 11%. Exceeding 6% MOF addition did not improve the uptake or performance. Microstructure characterization highlighted the formation of calcite, aragonite, and calcium silicate hydrate and the consumption of calcium hydroxide. The MOF-incorporating concrete can be used in construction applications to mitigate CO2 emissions while maintaining concrete performance.

Hydraulic characteristics and vegetation performance of the Yellow River sediment modified by biochar

The Yellow River sediment (YRS) is an important potential soil resource for the mine land reclamation and ecological restoration in the arid regions of northern China. However, it has the shortcomings of poor water-holding capacity and needs to be modified urgently. Therefore, two types of biochar, namely rice husk biochar (RHB) and coconut shell biochar (CSB), were utilized in this study to modify the YRS and compared with rice husk ash (RHA). Some engineering properties of the modified YRS (MYRS), including pore structure, water retention, permeability, and vegetation performance, were investigated by considering the effects of biochar types and dosages. Results showed that the addition of the three materials decreased the bulk density of the YRS and increased the volume of extremely micro pore (d<0.3 µm), as well as the effective porosity and capillary porosity, thus contributed to an increase in the water-holding capacity of the sediment. Among the three conditioners, RHB is optimal choice for improving the water-holding capacity of YRS. Furthermore, the effect becomes more pronounced with increasing application rates. With the addition of the three materials, the permeability coefficients of MYRS gradually decreased, while the water retention rate during evaporation significantly increased. The pot experiment showed that the three conditioners all had significant promoting effect on the growth of oats. In particular, compared to plain soil, the total biomass of oats grown for 21 days increased by 17.46%, 32.14%, and 49.60% after adding 2%, 4%, and 8% RHB, respectively. This study introduces a new approach for using YRS as planting soil in arid and semi-arid areas of China to facilitate mine ecological restoration.

Three-Dimensional Spatial Microscopic Characteristics and Developmental Influencing Factors of Tight Gas Layers in Hangjinqi Prospect Area, Ordos Basin, China

The unconventional tight oil and gas resources in the Xinzhao East belt of the Hangjinqi Prospect area in the Ordos Basin of China are abundant. However, the reservoir’s internal storage space is complex, and the microscopic pore throat structural features are not well recognized, which has led to some trouble in the deployment of oil and gas exploration. To reveal the microscopic characteristics of the dense sandstone gas layer in the first member of the Lower Stone Box Formation of the D-well Zone in the Xinzhao East belt of the Hangjinqi Prospect area, a three-dimensional space digital core was built, and the stored set spatial data were extracted, based on rock sheet and coring data and X-CT scanning technology. Quartz grain size was segmented and analyzed based on an adaptive approach. The microscopic characteristics of the gas layer in the studied section and the factors influencing its development were studied, combining the use of a field emission scanning electron microscope, helium porosimeter, and gas permeability meter. We found that in the studied section, the porosity is relatively high, the pore throat size is large, and the pore permeability correlation is good. The reservoir space, which consists of intergranular pores, intragranular pores, and microcracks at the grain edges in the study area, is characterized by a complex distribution pattern. Within the gas layer, isolated pores are connected by microcracks to form a network of reservoir spaces, which increases the pore throat size, enhances the connectivity of the pore throat, and makes the microscopic characteristics of the reservoir space better. The first member of the Lower Stone Box Formation could be an advantageous reservoir. Hole–throat connectivity is poor because of the gas layer having underdeveloped primary pores, the blockage of pores by unstable minerals (kaolinite, etc.), and poorly connected pore throats based on insoluble mud cementation. The high content of quartz brittle minerals and the development of natural microcracks within the gas formation are favorable conditions for fracking development. The quartz grain size within the gas layer is positively correlated with the pore throat size, which suggests that the quartz grain size somewhat influences the microscopic characteristics of the reservoir space. This comprehensive study shows that the methodology of the study is more advantageous than traditional methods in the fine and three-dimensional spatial characterization of the microstructure of dense sandstone reservoirs. The research results of this paper have certain guiding significance for further reservoir evaluation and advantageous reservoir prediction in the Hangjinqi Prospect area in the Ordos Basin. We also provide the basis for the subsequent efficient development of the gas reservoir.

Apelin is a peptide increasing tolerance of organs and cells to ischemia and reperfusion. The molecular mechanism (the review)

Ischemic-reperfusion injuries of organs underlie such common pathologies as ischemic stroke and myocardial infarction and are the cause of death and disability in the population. In addition, ischemic lung damage is observed in pulmonary embolism. Advances in transplantology, as well as the widespread use of coronary artery bypass grafting, raise the problem of ischemia and reperfusion of organs during these manipulations. Progress made over the past three decades in the treatment of stroke and acute myocardial infarction (AMI) has slowed in recent years. Since patients with stroke and AMI are admitted to the hospital with ischemic damage to the brain or heart, it is no longer possible to influence its formation. However, it is possible to affect reperfusion injury to organs. Significant progress in improving the efficiency of kidney transplantation, in the treatment of stroke, pulmonary embolism and AMI can be achieved through the development of new drugs that can effectively prevent reperfusion damage of organs. Synthetic analogues of apelin with a long half-life can become prototypes of drugs with similar action. It has been found that apelins can increase the tolerance of the heart, brain, kidneys and lungs to ischemia/reperfusion (I/R). Apelins inhibit apoptosis and activate cardiomyocyte autophagy. The neuroprotective, cardioprotective, renoprotective, and pulmonoprotective effects of apelins are realized through intracellular signaling, including protein kinases, a mitochondrial variable permeability pore, and ATP-sensitive K+ channels. Enzyme-resistant analogues of apelin are promising peptides for the treatment of AMI, stroke, and I/R damage to the lungs, and kidneys.

Estimation of pore structure and permeability in tight carbonate reservoir based on machine learning (ML) algorithm using SEM images of Jaisalmer sub-basin, India

Analyzing the pore structure in carbonate reservoirs plays a crucial role in predicting fluid flow characteristics within these formations. The goal of the study was to use machine learning techniques for pore structure analysis and estimation of permeability in carbonate reservoirs. We implemented these algorithms by examining 2D scanning electron microscope (SEM) images of carbonate samples from the Jaisalmer sub-basin captured at various magnifications. In the initial stage of the analysis, various binarization algorithms were applied to determine carbonate sample porosity. Among these algorithms, the MaxEntropy algorithm gave a porosity value closely aligned with those obtained through petrography analysis. We employed the watershed algorithm to find the pore network parameters of carbonate samples at various magnifications. We observed that changes in magnification affected pore network parameters, resulting in a reduction in pore size distribution, throat radius, and grain size. Subsequently, we employed the numerical lattice Boltzmann method (LBM) to estimate the permeability of carbonate samples and compared to values derived from well logs. We employed machine learning (ML) algorithms, specifically Artificial Neural Network (ANN) and Support Vector Machine (SVM), to predict the permeability of carbonate samples. The input features for these models were the pore network parameters, while the LBM permeability values served as the output. We examine the prediction performance of these methods against the measured LBM permeability by conducting the error analysis and the coefficient of determination (R2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${R}^{2}$$\\end{document}) calculation. Our findings revealed that the ANN models outperformed the SVM models. Specifically, the ANN model displayed an impressive R2 value of 0.892, along with root mean square error (RMSE), mean squared error (MSE) and, mean absolute error (MAE) values of 1.927, 3.716 and 1.580, respectively. In contrast, the SVM model yielded an R2 value of 0.849, with RMSE, MSE and, MAE values of 2.324, 5.401 and, 2.166 respectively, when assessed on testing data of measured permeability. This study found that ANN is more dependable, robust, and precise than SVM in forecasting carbonate sample permeability.

Study on the Mechanism of Gas Intrusion and Its Transportation in a Wellbore under Shut-in Conditions

This paper presents a comprehensive study based on multiphase-seepage and wellbore multiphase-flow theories. It establishes a model for calculating the rate of gas intrusion that considers various factors, including formation pore permeability, bottomhole pressure difference, rheology of the drilling fluid, and surface tension. Experiments were conducted to investigate the mechanism of gas intrusion under shut-in conditions, and the experimental results were employed to validate the reliability of the proposed method for calculating the gas intrusion rate. Furthermore, this research explores the transportation rates of single bubbles and bubble clusters in drilling fluid under shut-in conditions. Additionally, empirical expressions were derived for the drag coefficient for single bubbles and bubble clusters in the wellbore. These expressions can be used to calculate gas transportation rates for various equivalent radii of single bubbles and bubble clusters. The initial bubble size of intrusive gas, the transportation speed of intrusive gas in the wellbore, the rate of gas intrusion, and variations in the wellbore pressure after gas intrusion were analyzed. Additionally, a method was developed to calculate the rising velocity of bubble clusters in water based on experimental results. The study reveals that the average bubble size in the bubble cluster is significantly smaller than the size of single bubbles generated from the orifice. When the viscosity of the drilling fluid is low, the transportation velocity of the bubble cluster exhibits a positive correlation with the average bubble diameter. When the average bubble diameter exceeds 1 mm, the bubble velocity no longer varies with changes in the bubble-cluster diameter. The research results provide theoretical support for wellbore pressure prediction and pressure control under shutdown conditions.

RELATIVE PERMEABILITY MODEL OF TWO-PHASE FLOW IN ROUGH CAPILLARY ROCK MEDIA BASED ON FRACTAL THEORY

In this paper, the gas-water two-phase flow characteristics of rock media are studied based on fractal theory and the relative roughness model, and the analytical model of gas-water relative permeability of rock pores with relative roughness is derived. Through numerical simulation, it is found that the maximum flow velocity in the rough microchannel is greater than the maximum flow velocity in the smooth microchannel, but the average flow velocity in the rough microchannel is less than the average flow velocity in the smooth microchannel. The theoretical model results show that the dimensionless permeability of gas-water two-phase flow is inversely proportional to the fractal dimension of relative roughness and tortuosity, and the relative permeability of gas-water two-phase flow is inversely proportional to the relative roughness. The correctness of the model is verified by comparing it with the relevant experimental data.

Synthesis of high-quality nano-H-ZSM-5 single crystals zeolite from montmorillonite and MTO catalytic studies

Clay is a rich aluminosilicate resource with unique advantages as a raw material for zeolites production. However, synthesizing nanosized single-crystalline zeolites through a simple approach using clay remains a significant challenge. In this paper, acid-washed montmorillonite (MSR) was used to prepare nano-H-ZSM-5 single crystals with high crystallinity, uniform grain size and permeable straight pores under the induction of a small amount of organic template tetrapropylammonium hydroxide (TPAOH). Through temperature-staged treatment, the nucleation and growth process of zeolite were decoupled, ultimately achieving precise control over the size of the nano-single crystals. Mechanistic study showed that the low-temperature aging process produces smaller structural units which probably derived from the geopolymer topology of the clay, providing more active sites for zeolite nucleation, leading to the rapid crystallization during the high-temperature process. The porous structure promotes material diffusion, inhibits aromatic cycling and reduces carbon formation in the pores. The large specific surface area and nanoscale multilayer pore structure delay carbon accumulation and increase carbon holding capacity. These properties make nano-ZSM-5 single crystals an excellent choice for high olefin selectivity and long catalytic life in the methanol-to-olefin reaction. This synthetic route provides a general strategy for preparing nanosized zeolite single crystals from clay.

INVESTIGATING THE RELATIONSHIP BETWEEN PORE CHARACTERISTICS, FRACTAL DIMENSION, AND PERMEABILITY OF LIMESTONE USING HIGH-PRESSURE MERCURY INTRUSION, SEM ANALYSIS, AND BP NEURAL NETWORK

In this study, limestone samples from a coal mine in the North China region were selected for analysis. High Pressure Mercury Intrusion (HPMI) and Scanning Electron Microscopy (SEM) experiments were conducted to explore the impact of pore characteristics and fractal dimension of limestone on permeability. Additionally, regression analysis and a Backpropagation Neural Network (BPNN) were employed to predict permeability. The results of this study reveal that the pore-throat distribution of the limestone samples is non-uniform, indicating significant heterogeneity. The difference of pressure curve morphology affects the permeability. Utilizing multivariate regression analysis, a relationship was established between permeability and parameters such as mean radius, porosity, and fractal dimension. Furthermore, the BP neural network was effectively employed to predict permeability values, with small discrepancies between predicted and measured values. This study establishes a link between microstructural attributes and macroscopic permeability providing a robust theoretical foundation for permeability assessment and engineering applications pertaining to limestone.

A novel apparent permeability model for shale considering the influence of multiple transport mechanisms

Changes in pore pressure during the extraction of shale gas lead to dynamic alterations in the pore structure and permeability, making it challenging to gain a comprehensive understanding of the flow behaviors of shale gas. The pore structure of shale is complex, with a variety of storage modes and gas transport processes constrained by a number of factors. For instance, when gas flows through a transport channel with a finite length, it is imperative to take into account the flow loss caused by the bending of inlet and outlet streamlines, prior models typically neglect the impact of end effects, resulting in an exaggerated estimation of the shale permeability. Furthermore, a decrease in pore pressure corresponds to an increase in the Knudsen number, resulting in the breakdown of the continuity assumption of the Navier–Stokes equation, this signifies the gradual shift of the transport regimes from continuum flow to other transport regimes. The gas flow process is nonlinear due to the alternating impact of multicomponent transport mechanisms and various microscale effects. In this paper, we presented a novel apparent permeability model for shale that incorporates the impact of real gas effect, end effects, transport regimes, adsorption, and effective stress. First, we assumed the channel for shale gas transport to be circular pore and calculated the viscosity under the influence of a real gas effect as well as the corresponding Knudsen number. Subsequently, building upon the foundation of the slip model, we introduce the influence of the end effects to establish a bulk phase permeability for shale, further considering the impact of surface diffusion. Then, the pore radius was quantified under the influences of adsorption and effective stress. Using the intrinsic correlation between permeability and pore radius as a bridge, a shale apparent permeability model was further derived. The model encompasses various transport regimes and microscale effects, replicating the gas flow behaviors in shale. The new model was verified through comparison with published experimental data and other theoretical models, while analyzing the evolution of apparent permeability. Additionally, this paper discusses the influence of various factors, including end effects, pore radius, internal swelling coefficient, sorption-induced strain, and model-related parameters on the shale apparent permeability.

Characteristics of pore structure and permeability prediction in binary blended pervious concrete

Characteristics of pore structure and permeability prediction in binary blended pervious concrete