Permeability Model Research Articles

Siliciclastic reservoir characterisation and geometric trend modelling for hydrocarbon quantification and uncertainty analysis: a case study of Doma field, Niger Delta basin, Nigeria

ABSTRACT Reservoir architecture delineation and understanding of heterogeneity in geological reservoir models are crucial for accurately estimating hydrocarbon reserves, production forecast, and recovery in an effective economic scenario. This work demonstrates the combination of statistical tools and geometric trend models for hydrocarbon quantification and uncertainty analysis in the Doma Field development. 3D seismic cube and five (5) well data were integrated to build structure, facies, and petrophysical models (total and effective porosity, water saturation, net-to-gross, and permeability). Eleven (11) hydrocarbon-bearing reservoirs were identified and modelled out of twenty-two (22) reservoirs (sand 1–1B2–5-IB1) delineated and correlated from the logs. The saturation height function (SHF) was generated to populate the water saturation model to mitigate capillary pressure build-up. The structural model shows that fault-dependent three-way closure dominated the field. The results of petrophysical analysis and modelling biased to the litho-facies models indicated an average effective porosity value between 20 and 37% and water saturation ranging from 0.1 to 0.5. The permeability model showed that the permeability value was greater than 100 mD. Based on uncertainty analysis, the low case, base case, and high case cumulative volumetric for oil is 43.63MMSTB, 56.72MMSTB, and 71.34MMSTB and for gas is 73.65BSCF, 96.3BSCF, and 120.59BSCF, respectively. The coefficient of variation computed from log-derived porosity varies from 0.14 in reservoir 1-IB1 to 0.44 in reservoir 14-IB2. Also, the coefficient of variation computed from the 3D model porosity varies from 0.21 in reservoir 2-IB1 to 0.45 in reservoir 14-IB2. Thus, the research study has created a bridge between statistical tools in quantifying reservoir model heterogeneity and established a reference model for siliciclastic reservoir heterogeneity classification and prediction in the area and development of reservoir parameters in the adjacent areas of the Niger Delta basin.

Characterization of Damage and Infiltration Modeling of Coal-Slurry Consolidation Mechanics Under Loaded Conditions

Coal seam gas drainage is a primary measure for mitigating coal and gas outburst hazards. Grouting sealing can form coal-slurry consolidated bodies, significantly improving the sealing quality of gas drainage boreholes and alleviating coal and gas outburst risks. Therefore, this study conducts triaxial loading and seepage experiments to analyze the mechanical failure characteristics and permeability variation of coal-slurry consolidated bodies under loading conditions following grouting sealing of gas drainage boreholes. Based on the “cube” model, a permeability model for the damaged coal-slurry consolidated body under loading conditions is established. The findings provide guidance for evaluating the leakage prevention performance of sealing materials in field engineering and optimizing the sealing efficiency of grouting materials. Future research may explore the damage and seepage evolution of coal-slurry consolidated bodies under various loading conditions and sealing material types.

Improving permeability modeling using artificial neural networks in Lower Safa sand reservoir, JG field, Abu El-Gharadig basin, Western Desert, Egypt

Predicting permeability along and between wells to obtain the 3D spatial distribution is challenging in reservoir modeling. Permeability measurements using core sampling are time-consuming and accord too limited subsurface coverage. This study presents a systematic approach based on artificial neural networks (ANNs) to integrate core data and well logs to overcome these challenges and construct a robust 3D permeability model for the Lower Safa sand reservoir, JG field, Abu El-Gharadig basin, Egypt. The routine core analysis was performed to determine the reservoir quality and heterogeneity. Core-log depth match was performed, and the influential well logs, including effective porosity, bulk density, and deep resistivity logs, were selected to build the permeability model. ANN is applied to integrate the core permeability with the logs to predict permeability logs in the two studied wells. The dataset is randomly split into training, validation, and testing sets to evaluate the model's performance, and different hyperparameters are tuned to improve the prediction accuracy. A detailed comparison between the conventional method and the proposed ANN approach is provided in this study. Results demonstrate that the proposed ANN model was able to improve the permeability prediction performance by capturing the complex relationships between permeability and well logging data. The model achieves outstanding performance, where the coefficient of determination (R2) between the predicted permeability and core permeability is 0.90, 0.91, and 0.88 for the training, validation, and testing datasets, respectively. The developed model was used to predict the permeability logs along the reservoir intervals of the two studied wells. Ultimately, the Sequential Gaussian Simulation algorithm was used to populate the predicted logs in 3D. The outcomes of the study will aid users of deep learning to make informed choices on the appropriate ANN models to use in clastic reservoir characterization for more accurate permeability prediction with limited available data.

Comparative Analysis of Caco-2 Cells and Human Jejunal and Duodenal Enteroid-Derived Cells in Gel- and Membrane-Based Barrier Models of Intestinal Permeability.

Intestinal absorption is a key toxicokinetics parameter. While the colon carcinoma cell line Caco-2 is the most used in vitro model to estimate human drug absorption, models representing other intestinal segments are developed. We characterized the morphology, tissue-specific markers and functionality of three human intestinal cell types: Caco-2, primary human enteroid-derived cells from jejunum (J2), and duodenum (D109) when cultured in the OrganoPlate® 3-lane 40 microphysiological system (MPS) or static 24-well Transwells™. In both conditions, J2 and D109 formed dome-like structures; Caco-2 formed uniform monolayers. In MPS, only Caco-2 formed tubules. Cells grown on Transwells™ formed a thicker monolayer. All cells and conditions exhibited expression of ZO-1 (tight junctions). Polarization markers Ezrin and Villin were highest in J2 and D109 in MPS, highest expression of Mucin was observed with J2. However, J2 and D109 exhibited poor barrier (70 kDa TRITC-dextran) in MPS, while robust barrier was recorded in Transwells™. Barrier function and drug transport were evaluated using caffeine, indomethacin, and propranolol. The gel lane in MPS acted as a blockade; only a small fraction crossed, even without cells. The permeability ratios were used to parameterize the probabilistic compartmental absorption model to determine whether in vitro data could reduce uncertainty. The most accurate prediction of the fraction absorbed was achieved with Transwell™-derived data from Caco-2, combined with the experimentally-derived segment-specific absorption ratios. The impact of this study includes demonstration that enteroid-derived cells cultured in MPS show most physiological morphology, but that studies of drug permeability in this MPS are challenging.

Pesticides’ Cornea Permeability—How Serious Is This Problem?

Background: A total of 348 pesticides from different chemical families (carbamates, organochlorines organophosphorus compounds, pyrethroids, triazines and miscellaneous) were investigated in the context of their cornea permeability and potential to cause eye corrosion. Methods: Multivariate models of cornea permeability based on compounds whose cornea permeability has been determined experimentally were proposed. The models, applicable to compounds across a relatively broad lipophilicity range (e.g., pesticides with octanol–water partition coefficient log P up to ca. 8), assume a reverse-parabolic relationship between cornea permeability and lipophilicity, expressed as XLOGP3; other main descriptors present in the models are log D at pH 7.4 and polar surface area (PSA). Results: It appears that the trans-corneal transport of all studied pesticides is possible to some degree; however, it is more difficult for the majority of highly lipophilic pesticides from the organochlorine and pyrethroid families. The same set of 348 pesticides was also evaluated for their eye-corrosive potential using novel artificial neural network models involving simple physico-chemical properties of the compounds (lipophilicity, aqueous solubility, polar surface area, H-bond donor and acceptor count and the count of atoms such as N, NH, O, P, S and halogens). Conclusions: It was concluded that eye corrosion is an issue, especially among the pesticides from organochlorine and organophosphorus families.

Preliminary Metabolomics and Determination of a Potent Anti-inflammatory Fraction of Freshwater Brown Algae

Objective: The study aims to perform preliminary metabolomics and identify the potent anti-inflammatory fractions from freshwater brown algae extract. Materials and Methods: The brown algae sample was harvested from the exposed rocks in Ebonyi River in Nigeria, and was subjected to cold maceration in a methanol-dichloromethane (2:1) solvent mixture for 72 hours, for extraction. The resulting extract was concentrated and subsequently fractionated via vacuum liquid chromatography (VLC) using solvent gradients of n-hexane and ethyl acetate. Acute toxicity was evaluated in Swiss albino mice according to Lorke’s method, with mortality rates employed to determine the LD50. The anti-inflammatory potential of the fractions was assessed using both in vitro (protein denaturation and heat-induced hemolysis assays) and in vivo (acetic acid-induced vascular permeability and xylene-induced edema) models. Doses of 50 and 100 mg/kg as well as 1 and 2 mg of the fractions (3:7, 5:5, 7:3) were administered orally and topical for the in vivo models respectively, while doses ranging from 62.5 to 1000 μg were used for the in vitro test. Dexamethasone was used as the positive control. High-performance liquid chromatography (HPLC) dereplication was employed to identify the phytoconstituents of the fractions. Results: Many anti-inflammatory compounds, including quercetin, ellagic acid and Kaempferol were identified in the fractions which would have accounted for the pronounced anti-inflammatory properties observed. Fraction 5:5 showed a superior anti-inflammation compared to dexamethasone in the xylene-induced edema model, although not statistically significantly different. Conclusion: These fractions, especially 5:5 can be further developed for the treatment of inflammation.

Permeability Benchmarking: Guidelines for Comparing in Silico, in Vitro, and in Vivo Measurements.

Permeability is a measure of the degree to which cells can transport molecules across biological barriers. Units of permeability are distance per unit time (typically cm/s), where accurate measurements are needed to define drug delivery in homeostasis and to model dysfunction occurring during disease. This perspective offers a set of community-led guidelines to benchmark permeability data across multidisciplinary approaches and different biological contexts. First, we lay out the analytical framework for three methodologies to calculate permeability: in silico assays using either transition-based counting or the inhomogeneous-solubility diffusion approaches, in vitro permeability assays using cells cultured in 2D or 3D geometries, and in vivo assays utilizing in situ brain perfusion or multiple time-point regression analysis. Then, we demonstrate a systematic benchmarking of in silico to both in vitro and in vivo, depicting the ways in which each benchmarking is sensitive to the choices of assay design. Finally, we outline seven recommendations for best practices in permeability benchmarking and underscore the significance of tailored permeability assays in driving advancements in drug delivery research and development. Our exploration encompasses a discussion of "generic" and tissue-specific biological barriers, including the blood-brain barrier (BBB), which is a major hurdle for the delivery of therapeutic agents into the brain. By addressing challenges in reconciling simulated data with experimental assays, we aim to provide insights essential for optimizing accuracy and reliability in permeability modeling.

Quantitative reservoir evaluation and hydrocarbon volumetrics :an integrated petrophysical and 3-D static modeling approach in ‘Hamphidex’ field, Niger-Delta, Nigeria

The viability and hydrocarbon volumetrics of the Hamphidex field reservoirs were evaluated using petrophysical analysis and three-dimensional (3D) static modeling of three key reservoir sands (X, Y, and Z). The petrophysical analysis involved detailed characterization of lithologies, net-to-gross ratios, porosity, hydrocarbon saturation, water saturation, and permeability. The volumetric attributes of the field were derived from the constructed 3D reservoir models. Two geostatistical methods—Sequential Gaussian Simulation (SGS) and Sequential Indicator Simulation (SIS)—were utilized for facies and property modeling, focusing on porosity and permeability. Comprehensive facies models and petrophysical property models were developed for each reservoir sand (X, Y, and Z), integrating 3D visualizations of facies distributions, porosity, permeability, water saturation, and fluid contact models. These models also included cross-sectional views, providing a detailed spatial representation of the reservoir's characteristics. Two main facies, sand and shale, were identified, with sand acting as the hydrocarbon reservoir. Well-log correlations in six wells (Hamdex-02, 06, 01, 05, 04 and 07) of the field show that sands X, Y, and Z have lateral continuity and their hydrocarbon potential varies between wells. Specifically, Sand ‘X’ contains hydrocarbons in Hamdex-05 and Hamdex-07, Sand ‘Y’ is hydrocarbon-rich in Hamdex-05, and Sand ‘Z’ shows hydrocarbon presence in Hamdex-06, Hamdex-05, and Hamdex-04. These hydrocarbons are confined within an anticlinal structural trap that closes on a fault. For Sand X, Y, and Z, porosity values range between 16 and 25%, permeability varies from 10 to 1600 mD, water saturation lies within 7 to 50%, and hydrocarbon saturation spans from 50 to 93%. The volumetric assessments from the build models showed that Sand X, Y and Z have Stock-Tank-Oil-Initially-In-Place (STOIIP) of 75.864, 8.566 and 80.177 Million Barrels (MMbbl) respectively. In addition to Sand Y STOIIP it also has Gas-Initially-In-Place (GIIP) of 14.870 Billion Standard Cubic Feet (Bscf). The analysis indicates that the field contains substantial hydrocarbon reserves, with the petrophysical properties confirming the reservoirs' high quality. These findings demonstrate that the field is economically viable and suitable for development, presenting a strong potential for successful exploitation.

Experimental investigation of gas seepage characteristics in coal seams under gas-water-stress function

Seepage experiences were conducted on coal samples with diverse levels of moisture content, gas pressure, and effective stress to investigate how gas seepage in a coal seam is affected by the interaction of gas, water, and stress. The results of the study revealed the intricate relationship between these factors and their impact on the permeability and seepage behavior of coal. The findings indicate that, with increasing gas pressure, the permeability of coal specimens containing different levels of moisture varies distinctly. When coal samples have low moisture content, their permeability displays a pattern of “increase - decrease - increase” as gas pressure increases. However, with the further increase of moisture content, the “increase-decrease” trend of permeability with the increase of gas pressure disappears. The relationship between permeability and effective stress can be modeled using either a quadratic or logarithmic function. On the other hand, the connection between permeability and moisture content, can be represented by a quadratic or exponential function. At low levels of moisture content, gas pressure has the most pronounced effect on permeability of coal samples, followed by moisture content and effective stress. Conversely, at high levels of moisture content, the most influential factor is moisture content, followed by gas pressure and effective stress. Finally, a model of permeability has been developed that takes into account the collective impacts of gas pressure, moisture content, and effective stress. The research outcomes can establish a basis for optimizing gas recovery from coal seams.

Permeability Model for Fractal Porous Media with Rough Capillary Walls

The pore space of a porous medium is typically considered to consist of a collection of curved capillaries with rough walls. A model describing roughness is established by applying fractal theory. As a result, a modified permeability model is derived theoretically, which is closely related to roughness. To validate this model, a new form of Kozeny–Carman (KC) equation is also developed for estimating permeability on a set of benchmark rock samples, and a good agreement was achieved in terms of small relative error between measured and predicted permeabilities. Therefore, we can conclude that pore roughness should not be ignored in predicting permeability. Although the improved KC equation can predict permeability effectively too, it is not practical as the KC constant is difficult to determine.

Data-driven predictive model of coal permeability based on microscopic fracture structure characterization

Data-driven predictive model of coal permeability based on microscopic fracture structure characterization

Instability mechanism and a fractal theory-based relative permeability model of immiscible two-phase displacement in rough fractures

The two-phase displacement in rock fractures is a critical scientific challenge in deep energy development projects, characterized by the intricate and dynamic flow patterns resulting from the complex fracture geometry and mutual interference between the two-phase fluids. The present study involves the construction of a three-dimensional rough fracture fine model using the fast Fourier transform and Gaussian distribution method. The phase field-finite element method is employed to simulate the dynamic displacement of water-oil flow and the evolution of the water-oil interface, aiming to investigate the impact of roughness, aperture, and wettability on the viscous fingering pattern observed in rough fractures. The numerical results indicate that the immiscible two-phase displacement presents a viscous fingering pattern at a high flow rate. Moreover, the greater the roughness is, the higher the number of fingering is, and the more volatile the change in displacement velocity is. The width of the wet-phase flow channel increases proportionally with the fracture aperture increasing. Furthermore, the morphology of immiscible two-phase interface within fractures is also influenced by the wetting angle, and the fingering, bifurcation, and crushing phenomena appear in the oil-wet state with the strong displacement interface instability. Finally, a fractal model of relative permeability for waterflooding in rough fractures is proposed based on the cubic law of flow and fractal dimension of aperture distribution, which has been validated through comparison with numerical results.

The seepage model for CO2 in Shale considering dynamic slippage, effective stress and gas adsorption

This paper first conducted a shale injection CO2 seepage experiment based on an improved single-vessel pressure pulse attenuation method. The experimental results reveal that the evolution pattern of shale permeability with respect to pore pressure can be divided into before and after phase change. The overall trend is that it first decreases and then increases, which is not a simple exponential form. The exponential fit of the permeability before and after the phase change alone is one-sided. A CO2 adsorption deformation test was subsequently conducted on shale under the same temperature and gas pressure conditions. The results revealed that with increasing CO2 pressure, the expansion and deformation of shale first increased but then decreased. The entire deformation process involves three deformation stages: a short compression stage, a slow expansion stage, and a stable deformation stage. The slip effect was corrected by combining adsorption expansion, effective stress, the real gas effect and the dynamic slip factor. The modified permeability model is more consistent with the relationship between permeability and pore pressure.

Heterogeneity and permeability estimation of pore-throat structure at different scales in deep tight sandstone reservoirs: A case study of Paleogene Hetaoyuan Formation in Anpeng area, Nanxiang Basin, China.

Clarifying the pore-throat size and pore size distribution of tight sandstone reservoirs, quantitatively characterizing the heterogeneity of pore-throat structures, is crucial for evaluating reservoir effectiveness and predicting productivity. Through a series of rock physics experiments including gas measurement of porosity and permeability, casting thin sections, scanning electron microscopy, and high-pressure mercury injection, the quality of reservoir properties and microscopic pore-throat structure characteristics were systematically studied. Combined with fractal geometry theory, the effects of different pore throat types, geometric shapes and scale sizes on the fractal characteristics and heterogeneity of sandstone pore throat structure are clarified. On this basis, the estimation model of tight sandstone permeability was established. The results indicate that the reservoir physical properties in the study area are poor, the pore types are mainly dissolved pores, and the pore size is mainly distributed in the nano to submicron range. The fractal dimension fitting curve obtained based on the non-wetting phase model has obvious turning points, indicating that the pore-throat structure has multi-scale characteristics. The turning point of fractal dimension divides the pore-throat structure of tight sandstone into large-scale pore-throats with good connectivity (reticular or beaded pore-throats) and small-scale pore-throats with poor connectivity (dendritic or capillary pore-throats), indicating that tight sandstone has binary pore structure characteristics. The geometry of large-scale pore-throat is complex, which is difficult to meet the self-similar characteristics, with the average fractal dimension is 3.72. The small-scale pore-throat morphology is close to the capillary and has obvious fractal characteristics, with the average fractal dimension is 2.22. There are many small pores and micropores in the reservoir, and the pore volume has a significant positive correlation with the total porosity of the rock, but the contribution to the permeability is low. The development degree of large-scale pore throat is an important factor affecting the physical properties of tight sandstone. The turning point radius of fractal curve and the comprehensive fractal dimension can be used as good indicators for permeability estimation.

NUMERICAL SIMULATION ON FLOW COUPLING IN A TRIPLE-FRACTURE NETWORK MODEL BASED ON FRACTAL GEOMETRY THEORY

This study presents numerical simulations on fluid flow under high stress and intense hydraulic activity and focuses on complex reservoirs with porous and fractured microstructures based on fractal geometry theory. A Triple-Fracture Network model, which includes pores, micro-fractures and macro-fractures, is categorized into fractal fracture networks and fractal pore systems based on fractal geometry theory. Using the Monte Carlo method, we construct macroscopic randomly distributed fractures to examine the impact of macro-fracture topological structures on flow dynamics. Fractal permeability models for micro-fracture and micro-pore systems are developed, incorporating variables such as fracture lengths and pore sizes. The proposed approach partitions porous media into macroscopically discrete fractures and microscopically characterized pores, utilizing fractal geometry theory to analyze hydro-mechanics coupling. The validity of the proposed model is confirmed through comparisons with analytical solutions and available models as well as the published field data. This results indicate that the spatial distribution of the effective stress and macroscopic fractures significantly affects the fractal dimensions of microscopic fractures and pores. It is found that the density of macro-fractures influences the fracture pressure, while the initial porosity and proportionality constant [Formula: see text] of micro-fractures impact the pressure distributions in the tested domains. It is found that the maximum length of micro-fractures correlates positively with permeability. This model introduces a novel perspective on random macro-fractures and fluid coupling in microstructures, enhancing the understanding of macro- and micro-hydrodynamics interactions.

Enhanced technique for analyzing waterflooding characteristic curve in water-bearing gas reservoirs considering the influence of water-sealed gas

ABSTRACT Considering the water-sealed gas effect in water-bearing gas reservoirs, this study integrates the heterogeneity coefficient (A) and the water influx coefficient (B) to quantify the water-sealed reserves precisely. Building upon this, a novel waterflooding characteristic curve equation is proposed by merging the material balance equation with the relative permeability model. Sensitivity analyses of the theoretical curve reveal that an increase in both the heterogeneity coefficient (A) and the water influx coefficient (B) exacerbates the water-sealed effect, prematurely and steeply elevating the waterflooding characteristic curve; this leads to a higher water-gas ratio. The results demonstrate that the proposed curve, which accounts for the water-sealed phenomenon, aligns well with production data throughout the entire development phase, enabling an effective assessment of gas reservoir exploitation efficiency and forecasting of water-gas ratios. This research enhances the versatility of waterflooding characteristic curve, improving the precision of water production forecasts and providing a robust foundation for water management strategies. Therefore, it has significant practical implications.

NUMERICAL MODEL OF DUST PERMEABILITY PROCESSES OF TEXTILE MATERIALS OF MINER’S SUIT

It is shown that improving the safety of miner’s suits is associated with the development of theoretical concepts of physical processes in textile materials. The current understanding of the passage of dusty air through a textile material does not always ensure the safety of miner’s suits. It has been established that one of the ways to solve this problem is to build and use digital twins of the processes of dust permeability of textile materials. The mechanisms of dusty air passage through a textile material are analyzed, a model of dust movement in the air flow in the immediate vicinity and structure of the textile material is proposed. A mathematical model of dust particle capture by structural elements of the fabric is compiled. Based on these ideas, a numerical model of dust permeability of a textile material is compiled, its solution is obtained using the example of fabric, an example of using the modeling results in calculating the dust permeability and dust capacity of textile materials is shown.

Organic Sunscreens—Is Their Placenta Permeability the Only Issue Associated with Exposure During Pregnancy? In Silico Studies of Sunscreens’ Placenta Permeability and Interactions with Selected Placental Enzymes

One of the functions of placenta is to protect the fetus against harmful xenobiotics. Protective mechanisms of placenta are based on enzymes, e.g., antioxidant enzymes from the glutathione S-transferases group (GST) or human N-acetyltransferase 2 (NAT2). Many organic sunscreens are known to cross biological barriers—they are detected in mother’s milk, semen, umbilical cord blood or placental tissues. Some organic sunscreens are able to cross the placenta and to interfere with fetal development; they are known or suspected endocrine disruptors or neurotoxins. In this study, 16 organic sunscreens were investigated in the context of their placenta permeability and interactions with gluthatione S-transferase and human N-acetyltransferase 2 enzymes present in the human placenta. Binary permeability models based on discriminant analysis and artificial neural networks proved that the majority of studied compounds are likely to cross the placenta by passive diffusion. Molecular docking analysis suggested that some sunscreens show stronger affinity for glutathione S-transferase and human N-acetyltransferase 2 that native ligands (glutathione and Coenzyme A for GST and NAT2, respectively)—it is therefore possible that they are able to reduce the enzyme’s protective activity. It was established that sunscreens bind to the studied enzymes mainly by alkyl, hydrogen bonds, van der Waals, π-π, π-alkyl and π-sulfur interactions. To conclude, sunscreens may become stressors affecting humans by different mechanisms and at different stages of development.

A new fractal permeability model for the dual-porous medium with a bundle of rough tree-like fracture networks

Shale gas reservoirs are typical dual-porous media where complex pore structures and fracture networks significantly impact gas transport. However, accurately predicting permeability in such media, especially complex fracture networks, remains challenging. The complex fracture network is modeled as of a bundle of rough tree-like fracture networks. The proposed permeability model comprehensively describes the structural characteristics of pores and fractures in shale gas reservoirs, including the fractal distribution of pore diameters and fracture apertures, the rough surface, and branching characteristics of fracture networks. Then, the model's accuracy is validated using reliable experimental permeability data. This model accurately predicts gas permeability and effectively describes gas transport characteristics in shale gas reservoirs with rough tree-like fracture networks. Each parameter has a clear physical meaning and avoids the use of empirical constants. Finally, sensitivity analyses are conducted to explore the effects of structural parameters on the permeability of dual-porous media. The results show that the permeability K of dual-porous media decreases exponentially with the increase in tortuosity fractal dimension Dtp of pores and surface fractal dimension Df of fractures, while it increases as a power function with increasing pore diameter fractal dimension Dp and fracture aperture fractal dimension Dh. The structural parameters of rough tree-like fracture networks significantly impact the permeability of dual-porous media. Increasing the aperture ratio γ, reducing the length ratio β, branching levels m, and the branching angles θ can significantly reduce gas flow resistance, decrease fluid kinetic energy loss, and increase the permeability of dual-porous media. This theoretical model is significant for enhancing permeability models of dual-porous media in shale gas reservoirs, offering reliable theoretical support for understanding gas migration and optimizing shale gas extraction.

An innovative coal permeability model based on elastoplastic mechanics: Development and verification

With the continuous mining of shallow coal resources, deep mining has increasingly become the norm. However, the migration mechanism of coalbed methane (CBM) in coal seams becomes exceptionally complex due to the combined influence of multiple factors in deep mining, posing considerable challenges to coal and gas co-mining. Therefore, studying the coal's mechanical behavior and seepage evolution mechanisms during deep mining is necessary. This study established a coal permeability model based on elastoplastic mechanics, considering the impacts of coal matrix destruction on the average fracture aperture. It assumed that the fracture aperture follows an exponential distribution and further introduced plastic strain to characterize the damage process in coal. The proposed permeability model was validated using the indoor experimental data. Subsequently, the control mechanisms of force-heat coordination effects on coal permeability were discussed, and the sensitivity of model parameters was analyzed. The results demonstrated that the established permeability model effectively described the evolution of coal permeability under the combined impacts of temperature and effective stress. Moreover, the fracture number ratio (η) and the influence coefficient of plastic strain increment on the average fracture aperture (β) not only connected the dilation of microfractures and plastic deformation in coal but also effectively reflected the relationship between permeability and plastic deformation during the failure process of coal. The results presented in this paper contributed to understanding the evolution of permeability during coal and gas co-mining, which should be of great significance for reducing coal and gas outburst hazards.