Determination Of Permeability Research Articles

APPROACH TO CREATION OF GEOLOGICAL AND RESERVOIR SIMULATION MODEL AND METHODS FOR HISTORY MATCHING OF RESERVOIR ENERGY STATE

Under conditions of complex geological structure and substantial share of hard-to-recover oil reserves, reservoir simulation is a key tool in reservoir management. Direct problems solved by reservoir simulation include forecasting of the production performance, control and management of reservoir development, and localization of residual oil reserves. Inverse problem solution is useful for updating the knowledge of geological structure, reservoir quality, and historical production data by means of history matching. The quality of history matching is fundamental to ensure reliable future forecasts and localization of residual oil zones. The main approaches to appropriate history matching rely on analysis and adjustment of well logging and geological parameters, as well as checking and correction of errors, inadequate historical data, application of physics-based and reasonable approaches and tools. The prerequisite for adequate history matching and predictive ability of the resultant reservoir simulation model is the compliance of simulated and actual energy state of the reservoir. In this paper, the initial stage of reservoir simulation is performed, the approach to history matching of reservoir energy state aimed at improving the quality of further predictions is described as exemplified by one of the production areas of Russian oil field. The main causes of poor history match of formation and bottomhole pressures are revealed. These causes are grouped as follows: — geological causes/reservoir quality, which include permeability field distribution, reservoir connectivity, and determination of rock and fluid compressibility;— technical causes (during reservoir simulation), that is model limitations in case of larger areas, the need to use sector models, consideration of buffer region;— technological causes, including inadequate historical data or lack of data, detection of behind-the-casing flows and production casing leaks in wellbore, etc. For each group of factors that have a substantial impact on reservoir pressure, recommendations and methods of energy state history matching on geological and reservoir simulation models are provided, examples are given.

Integrating Experimental and Theoretical Investigations of Porous Graphite Materials with Scanning Electron Microscope Image Processing

Accurate determination of fractal dimension (FD) and permeability of porous graphite materials (PGM) is essential for applications like porous aerostatic bearings (PABs). This study addresses the need for improved measurement methods by employing image processing and computer vision (IPCV) techniques to enhance FD and permeability accuracy. We aimed to refine these measurements by analysing the effects of image size and magnification on accuracy. The research developed theoretical models based on fractal theory, Darcy's law, and a modified Hagen-Poiseuille gas equation to evaluate these effects. A dual-path X-ray imaging detection system was used for experimental validation. The gauge pressure was varied across the surface of the PGM and volume flow rate was measured. MATLAB was utilized for IPCV, enabling precise FD determination and underscoring the importance of image parameters. Results showed that FD values stabilize at specific image sizes and magnifications, improving accuracy. Linear relationships between pressure gradient and volume flow rate were observed, with permeability stabilizing at high pressures. Porosity values varied among materials: Toyo Carbon (15%), SGL Graphite (17%), Super Carbon Graphite (27%), and poplar porous (30%). FD obtained through theoretical and scanning electron microscope (SEM) methods had a maximum error of 0.08. The study also found a positive correlation between relative density and image grayscale at the macroscopic level. The findings emphasize the importance of optimizing image size and clarity for accurate PGM analysis, providing crucial insights for PAB design and other advanced applications.

Numerical Determination of Anisotropic Permeability for Unconsolidated Hydrate Reservoir: A DEM–CFD Coupling Method

Numerical Determination of Anisotropic Permeability for Unconsolidated Hydrate Reservoir: A DEM–CFD Coupling Method

The Impact of Catalyst Layer Fabrication Procedure on Layer Morphology, Transport Properties and Performance in Low-Temperature PEM Fuel Cell

Hydrogen mobility represents a progressive, low carbon imprint option for the replacement of internal combustion engines. A core of this technology is low-temperature fuel cell with proton-exchange membrane (LTPEMFC), using hydrogen and atmospheric oxygen as fuel and oxidant, respectively. The membrane-electrode assembly (MEA) which makes up a cell consists of polymer electrolyte membrane, cathodic and anodic catalyst layers and carbon-based porous gas-diffusion layers. LTPEMFC require Pt catalyst on both the anode and the cathode in non-negligible total amount, increasing investing costs for stack unit. In order to maximise fuel cell performance, the formation of three-phase boundary has to be achieved during deposition of catalyst layers, interconnecting Pt nanoparticles on carbon support and ionomer with membrane in complex, porous structure. The quality of catalyst layer determines to high degree final MEA performance.Catalyst layers can be deposited either on gas-diffusion layers or onto the membrane, with latter being considered a more advantageous and feasible approach. Deposition itself can be realised by various methods, including airbrush spraying, decal printing, doctor blade deposition from paste and, most often used nowadays, ultrasonically-assisted spray coating. Each of these methods brings its own advantages and disadvantages, though the common problem of these methods is low suitability for serial production. On the other hand, the quality of so-prepared catalyst layers is sufficient. Methods for large-capacity coating of catalyst layers, especially roll-to-roll technology have exactly opposite pros and cons, high output but unsatisfactory layer quality. An interesting alternative to state-of-the-art catalyst layer fabrication procedures is inkjet printing.Inkjet printing is a well-established technology, though the application in LTPEMFC field brings various issues, mainly connected to quality of layers and prevention of nozzle-clogging during the deposition. Solving of these issues, however, will result in technology suitable for catalyst layer printing, combining high production throughput, very good reproducibility, minimal losses of the ink, suitability to additive manufacturing and possibility of printing specific geometries with gradient layer thickness. Accordingly, the goal of this study is the comparison of catalyst layers, deposited onto the membrane by ultrasonically-assisted spray coating and inkjet printing, in terms of morphology, electric conductivity, permeability and performance in LTPEMFC, using commercially-available materials for layer fabrication.Catalyst layers of the same composition and Pt loading were deposited by either ultrasonically-assisted spray coating or inkjet printing onto FTO conductive glass for the determination of electric conductivity, onto gas-diffusion layer for permeability determination in Loschmidt cell and FIB-SEM morphology studies and onto the membrane for the fabrication of MEA and evaluation of its performance in LTPEMFC. Characterisation of layers deposited on materials above underlined feasibility of inkjet printing for catalyst layer fabrication. In comparison with sprayed layers, layers prepared by inkjet printing tend to be thinner, more homogenous and compact. This results in superior electric conductivity but lower permeability at the same time. Single cell tests proved that performance of inkjet-printed layers is at least on par with sprayed ones, surpassing them with optimised ink composition and Pt loading. Overall, inkjet printing technology is a highly attractive technology for industrial catalyst layer production with great possibilities for contributing to decrease LTPEMFC unit’s investment costs.This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 958174. This project is co-financed from the state budget by the Technology agency of the Czech Republic under the M-ERA.Net Programme, project No. TH80020006. This work was supported by the project "The Energy Conversion and Storage", funded as project No. CZ.02.01.01/00/22_008/0004617 by Programme Johannes Amos Commenius, call Excellent Research. This project is co-financed with tax funds on the basis of the budget passed by the Saxon state parliament.

Novel formulation of Slichter’s model for permeability determination in unconsolidated materials: a critical review through field data

ABSTRACT Slichter’s model is a theoretical model that can be used for quantifying the permeability of non-cohesive materials. An inaccurate form of the equation has prevailed, undermining this model, which has been considered unreliable. This paper revises Slichter’s work and proposes a corrected formulation of his equation by redefining key parameters such as the referential grain size, the porosity function, and the area of the pores. This approach was tested for poorly graded sands and well-graded sandy gravels in northern Croatia and a literature control group of heterogeneous sediments. The results were compared with permeabilities determined from: (1) pumping and slug tests, and (2) the well-established Hazen’s experimental and Kozeny-Carman theoretical formulae. High correlativity between the different methods and with the field results confirmed the validity of the corrected Slichter’s equation for predicting the permeability of non-cohesive materials, regardless of their gradation and mean geometric grain size.

Determination of air permeability of buildings

The air permeability of the building determines the level of energy efficiency of the building. The regions of the European Union are approaching NZEB standards and passive house standards. The Ukrainian regulatory framework for airtightness does not meet European standards for energy-efficient buildings and will require updating, as there will be an increase in the wind permeability of the building, and the increase is possible to the normatively permissible value, increased air permeability and energy efficiency. The permeability is expressed by the value of the air flow in cubic meters per year per square meter of the area of the outer shell of the booth when there is a pressure difference in the internal air of 50 Pa. Ait permeability will need to be specified by parameter q50 [m3/(h·m2)] instead of n50 [h – 1]. All countries of the European Union may use the q50 [m3/(h·m2)] parameter in their standards. Exclusions are Lithuania and Ukraine, where the actual air permeability is determined by the parameter n50 [h – 1]. Based on the Ukrainian standard for air permeability, air permeability is calculated by n50 [h – 1]. For energy efficiency class C, values n50 < 2.0 [h – 1] are allowed, which is approximately the same value as q50 < 5.0 [m3/(h·m2)]. Following the Lithuanian standard, which also corresponds to the vicoristics n50, where n50 < 1.0 h – 1, which is approximately the same value as q50<2.5 [m3/(h·m2)]. It is proposed to establish new standard values for the air permeability and energy efficiency in line with European standards. The results of penetration tests of 24 objects of different heating volumes and energy efficiency classes were analyzed. It’s shown that lovering the energy efficiency class disharmonises the n50 and q50 values. The results allow proposal to set the normative value n50 < 2.5

Experimental Permeability and Porosity Determination of All-Oxide Ceramic Matrix Composite Material.

This paper presents an investigation into the water permeability of an all-oxide ceramic matrix composite. To determine the parameters and characterize the water permeability of the ceramic composite material, an experimental study was carried out in which a dedicated test rig was constructed and commissioned. A total of five different configurations of composite tubes were tested. They differed in fibre roving strength, winding angle, fibre bundle arrangement during winding, and matrix grain size distribution. To better understand the internal structure of the analysed ceramic matrix composite material, the experimental study used scanning electron microscopy for microstructure and porosity observation. The tested tubes will be used as liners in an oxy-combustion chamber in future studies. The experiments obtained new and interesting results regarding the water permeability of the ceramic matrix composite with different structural parameters. It was also observed that, as with some porous materials, the permeability of ceramic matrix composites decreases with time as more and more liquid is pressed through it.

Transient Pressure Behavior of CBM Wells during the Injection Fall-Off Test Considering the Quadratic Pressure Gradient.

Conventional coalbed methane (CBM) reservoir models for injection fall-off testing often disregard the quadratic pressure gradient's impact. This omission leads to discrepancies in simulating the transient behavior of formation fluids and extracting critical reservoir properties. Accurate determination of permeability, storability, and other properties is crucial for effective reservoir characterization and production forecasting. Inaccurate estimations can lead to suboptimal well placement, ineffective production strategies, and ultimately, missed economic opportunities. To address this shortcoming, we present a novel analytical model that explicitly incorporates the complexities of the quadratic pressure gradient and dual-permeability flow mechanisms, prevalent in many CBM formations where nanopores are rich, presenting a kind of natural nanomaterial. This model offers significant advantages over traditional approaches. By leveraging variable substitution, it facilitates the derivation of analytical solutions in the Laplace domain, subsequently converted to real-space solutions for practical application. These solutions empower reservoir engineers to generate novel type curves, a valuable tool for analyzing wellbore pressure responses during injection fall-off tests. By identifying distinct flow regimes within the reservoir based on these type curves, engineers gain valuable insights into the dynamic behavior of formation fluids. This model goes beyond traditional approaches by investigating the influence of the quadratic pressure gradient coefficient, inter-porosity flow coefficient, and storability ratio on the pressure response. A quantitative comparison with traditional models further elucidates the key discrepancies caused by neglecting the quadratic pressure gradient. The results demonstrate the proposed model's ability to accurately depict the non-linear flow behavior observed in CBM wells. This translates to more reliable pressure and pressure derivative curves that account for the impact of the quadratic pressure gradient.

A Novel Finite Element-Based Method for Predicting the Permeability of Heterogeneous and Anisotropic Porous Microstructures.

Permeability is a fundamental property of porous media. It quantifies the ease with which a fluid can flow under the effect of a pressure gradient in a network of connected pores. Porous materials can be natural, such as soil and rocks, or synthetic, such as a densified network of fibres or open-cell foams. The measurement of permeability is difficult and time-consuming in heterogeneous and anisotropic porous media; thus, a numerical approach based on the calculation of the tensor components on a 3D image of the material can be very advantageous. For this type of microstructure, it is important to perform calculations on large samples using boundary conditions that do not suppress the transverse flows that occur when flow is forced out of the principal directions. Since these are not necessarily known in complex media, the permeability determination method must not introduce bias by generating non-physical flows. A new finite element-based method proposed in this study allows us to solve very high-dimensional flow problems while limiting the biases associated with boundary conditions and the small size of the numerical samples addressed. This method includes a new boundary condition, full permeability tensor identification based on the multiscale homogenization approach, and an optimized solver to handle flow problems with a large number of degrees of freedom. The method is first validated against academic test cases and against the results of a recent permeability benchmark exercise. The results underline the suitability of the proposed approach for heterogeneous and anisotropic microstructures.

An improved convolutional neural network for predicting porous media permeability from rock thin sections

Permeability prediction is a crucial aspect of investigating fluid flow capacity in porous media, and rapidly predicting the permeability of rock thin sections aids in reservoir assessment. In recent years, significant progress has been made regarding the use of deep learning for predicting porous media permeability, effectively overcoming the limitations associated with time-consuming conventional permeability determination methods. To address the issues of low prediction accuracy and insufficient generalization capability of previous permeability prediction models, this study proposes an improved convolutional neural network for porous media permeability and applies it to predict the permeability of rock thin sections. Given the difficulty of obtaining a large amount of rock thin section data, we synthetically generated 1000 binary images of porous media and calculated the corresponding permeability labels using computational fluid dynamics. These data were used as foundational data for training the model. The proposed model achieved accurate and efficient permeability prediction of porous media with a correlation of 0.9667 on testing set. Simultaneously, we employed class activation mapping technology to visualize the permeability prediction process of the neural network, thereby elucidating the working principles of the neural network during porous media permeability prediction. Subsequently, based on an optimally pretrained neural network, transfer learning was utilized to predict the permeability of rock thin sections, which achieved a correlation of 0.9032. Our study extends the rock thin section applications and provides technical support for reservoir evaluation.

Resonant cavity method based on RF measurement and simulation for measuring complex permittivity or permeability of RF absorbing materials

Accurate measurement of complex permittivity and/or permeability of radio-frequency (RF) absorbing materials is essential to predict the performances of higher-order-mode damping in damped accelerating cavities or in vacuum chambers. We propose an improved resonant cavity method that can be used as a complement to the widely used Nicolson–Ross–Weir method for measuring the RF characteristics of materials. The conventional resonant cavity method is based on the cavity perturbation theory. However, the measurements are inaccurate when losses in the materials are large. The improved method we propose determines the complex permittivity or permeability of materials from the measured resonant frequencies and Q factors based on eigenmode simulations. Because the reliability on the eigenmode calculation for RF cavities with lossy materials has become sufficiently reliable, determination of complex permittivity and permeability can be achieved using such a simulation software. We demonstrate this method using ferrite HF70 (TDK Corp.), which is useful for RF absorbers in damped accelerating cavities or in vacuum chambers.

Determining relative permeability and capillary pressure from mixed-wet core floods

The main goal of this paper is a laboratory method development for determining the capillary pressure and relative permeability from coreflooding test specifically for mixed-wet rocks. Previously, the steady-state transient test (SSTT) was designed to determine both relative permeability (Kr) and capillary pressure (Pc) from a single steady-state coreflood by using the transient data of routine steady-state tests. On the contrary to the previous works, where SSTT was developed for completely hydrophobic or hydrophilic outcrop cores, this paper determines Kr and Pc for mixed-wet cores. Depending on the capillary pressure equation applied, the mathematical model for two-phase flow in mixed-wet rocks contains one or two extra constants, so some extra measurements must be taken during SSTT, to determine Pc and Kr curves. We change the experimental protocol by establishing a uniform initial saturation Swi by evaporation method. We also include bump floods at two high rates for the alternative determination of saturation and relative permeability for residual oil. A new inverse solver determines the set of model constants that employs van Genuchten's Pc formula and a vaporization procedure for initial core saturation. The number of resulting model coefficients is equal to seven and matches the dimension of the measured data array for mixed-wet cores.The developed SSTT for mixed-wet rocks is applied and validated for both high-salinity (HS) and low-salinity (LS) waterfloods. Strong agreement between laboratory steady-state, transient, and bump-flood data and those obtained by mathematical modelling – R2 is above 0.99 for steady-state data and above 0.9 for transient data - validates the proposed SSTT procedure and inverse solver for mixed-wet cores and HS and LS waterfloods. Our findings indicate that low salinity has a greater effect in expanding the range of positive capillary pressure compared to high salinity. This suggests an increase in water-wettability as the salinity decreases.

Breaking deep epicotyl physiological dormancy in C hionanthus retusus (Oleaceae) seeds

Given that the cause and the method of dormancy release in Chionanthus retusus seeds are unclear, in this study, C. retusus seeds with a hard endocarp (seed dispersal unit) were used for endocarp permeability determination, germination test after endocarp removal and isolated embryo culture to detect the cause of radicle dormancy. Endosperm removal, cold moist stratification, warm moist stratification and GA3 treatment of rooted seeds were used to detect the cause of epicotyl dormancy. The results indicated that C. retusus seeds have non-deep physiological dormancy and deep epicotyl physiological dormancy, the release of which was closely related to the length of the emerged radicle. Rooted seeds with a radicle length < 3 cm could not be effectively released from epicotyl physiological dormancy by endosperm removal, GA3 soaking or cold/warm stratification treatments, whereas those > 3 cm could be significantly promoted for release from epicotyl physiological dormancy by endosperm removal and cold moist stratification treatments. The highest shoot emergence rate of rooted seeds (radicle length > 3 cm) was achieved after 120 days of cold moisture stratification treatment. These results could improve our understanding of seed dormancy and promote the conservation and use of C. retusus.

INVESTIGATE OF INFLUENCE PERFORATED PLATE ON DETERMINATION OF TRANSVERSAL PERMEABILITY ON REINFORCED FIBER

Polymeric composite materials can be build in different forms, resulting in different mechanical properties, with numerous industrial applications. Traditionally, they have been largely used in the automotive, naval and aerospace industries. A major concern in polymeric composites manufacture is related with the determination and control of the reinforcement and resin physical properties. They are responsible for the final composite mechanic properties and, if not correct defined, will result in defective composites. Reinforcement permeability is one of these physical properties that, in some cases, are difficult to be kept within the project specification. More specifically, for the case of the transverse permeability, its corrected determination is reported in literature as being considerably more difficult to experiment than the in-plane permeability. The most common experiment for transverse permeability determination is built with a cylindrical mold on which the reinforcement is positioned (and compressed) between two perforated plates. A fluid is forced transversely through the reinforcement, volumetric flow rate and pressure drop are measured, and the Darcy's Law is used to determine the permeability. In this experiment, flow is assumed rectilinear, and the holes of the perforated plates are ignored in the Darcy equation. It is known that size, number e position of these holes may influence the permeability determination, however this problem is not commonly discussed in literature. In this work it is presented a numerical study about the influence of the geometry of the perforated plates on the corrected determination of the reinforcement transverse permeability. The reinforcement region is molded as a porous medium and the two fluid flow (air + resin) is formulated with the Volume of Fluid (VoF) method. GMSH software was used to created and discretize the geometry and OpenFOAM software, more specifically using the interFoam solver, was used to solve the flow problem, determining pressure drop and flow rate inside the mold. Results have shown that correct determination of the transverse permeability is highly dependent on perforate plates geometry.

Recycled Polypropylene/Strontium Ferrite Polymer Composite Materials with Electromagnetic Shielding Properties.

This paper presents the obtaining and characterization of recycled polypropylene/strontium ferrite (PP/SrFe12O19) polymer composite materials with applications in the electromagnetic shielding of vehicle interiors (mainly automotive electronics-carcasses) from the electromagnetic radiation emitted mainly by exterior sources-electrical lines and supply sources-in terms of the development of the new electrical vehicles. With this aim, suitable polymer composite materials were developed using SrFe12O19 filler in two forms (powder and concentrate). The recycled PP polymer and composite materials with a PP/SrFe12O19 weight ratio of 75/25 and 70/30 were obtained in two stages, i.e., pellets by extrusion and samples for testing through a melt injection process. The characterization of the obtained materials took into account the requirements imposed by the desired applications. It consisted of determining the mechanical and dielectric properties, and microstructure analyses, along with the determination of the resistance to the action of a temperature of 70 °C, which is higher than the temperatures created during the summer inside vehicles. The performance of these materials as electromagnetic shields was assessed through functional tests consisting of the determination of magnetic permeability and the estimation of the electromagnetic shielding efficiency (SE). The obtained results confirmed the improvement of the mechanical, dielectric, and magnetic properties of the PP/SrFe12O19 composites compared to the selected PP polymers. It is also found that all the composite materials exhibited reflective shielding properties (SER from -71.5 dB to -56.7 dB), with very little absorption shielding. The most performant material was the composite made of PP/SrFe12O19 powder with a weight ratio of 70/30. The promising results recommend this composite material for potential use in automotive shielding applications against electromagnetic pollution.

[18F]2-fluoro-2-deoxy-sorbitol ([18F]FDS) PET imaging repurposed for quantitative estimation of blood-brain barrier permeability in a rat model of Alzheimer's disease

Numerous studies suggest that blood-brain barrier (BBB) dysfunction may contribute to the progression of Alzheimer's disease (AD). Clinically available neuroimaging methods are needed for quantitative "scoring" of BBB permeability in AD patients. [18F]2-fluoro-2-deoxy-sorbitol ([18F]FDS), which can be easily obtained from simple chemical reduction of commercial [18F]2-fluoro-2-deoxy-glucose ([18F]FDG), was investigated as a small-molecule marker of BBB permeability, in a pre-clinical model of AD using in vivo PET imaging. Chemical reduction of [18F]FDG to [18F]FDS was obtained with a 100% conversion yield. Dynamic PET acquisitions were performed in the APP/PS1 rat model of AD (TgF344-AD, n=3) compared with age-matched littermates (WT, n=4). The brain uptake of [18F]FDS was determined in selected brain regions, delineated from a coregistered rat brain template. The brain uptake of [18F]FDS in the brain regions of AD rats versus WT rats was compared using a 2-way ANOVA. The uptake of [18F]FDS was significantly higher in the whole brain of AD rats, as compared with WT rats (P<0.001), suggesting increased BBB permeability. Enhanced brain uptake of [18F]FDS in AD rats was significantly different across brain regions (P<0.001). Minimum difference was observed in the amygdala (+89.0±7.6%, P<0.001) and maximum difference was observed in the midbrain (+177.8±29.2%, P<0.001). [18F]FDS, initially proposed as radio-pharmaceutical to estimate renal filtration using PET imaging, can be repurposed for non-invasive and quantitative determination of BBB permeability in vivo. Making the best with the quantitative properties of PET imaging, it was possible to estimate the extent of enhanced BBB permeability in a rat model of AD.

Integrating transient pressure and flow data for determination of hydraulic permeability and specific storage of a shale sample: Experimental tests and sensitivity analysis

This paper describes a comprehensive investigation to accurately determine the hydraulic permeability k and the specific storage Ss of a shale sample. One-dimensional pressure transient tests were conducted on a cylindrical sample under various levels of pore and confining pressures. For the boundary conditions, the upstream pressure was kept constant using a syringe pump, and the downstream storage was minimized for reducing the test duration. Both the downstream pressure and the upstream fluid flow into the sample were continuously recorded throughout the transient period. To estimate the hydraulic properties, the curve fitting technique was applied to the pressure and flow data using theoretical curves. We found that the pressure curve was sensitive to the ratio of hydraulic permeability to the specific storage (k/Ss), but not sufficient to determine the individual components (k and Ss). The upstream flow curve was sensitive to the specific storage but less sensitive to the permeability. Based on our sensitivity analysis, we present a combination of two objective functions of flow and pressure data to optimize both hydraulic properties with reasonable uncertainty. An alternative is to first use the flow data to determine Ss and then use pressure data with the predetermined Ss to obtain the remaining k.

DETERMINING THE PROPERTIES OF ROCK SAMPLES USING DEEP MACHINE LEARNING

Porosity, absolute permeability, and diffusion coefficient are crucial characteristics governing fluid flow in the porous media of geological formations. Determining these properties traditionally involves resource-intensive and time-consuming processes. However, with the advancement of deep learning methods in the last 3–4 years, artificial neural networks have gained significant traction in predicting the transport properties of the fluid-porous medium system and the geometric characteristics of porous samples based on their images. This approach allows for the rapid determination of these properties with acceptable accuracy. The aim of this article is to conduct a scientific review of literature from open sources on the deter-mination of absolute permeability, diffusion coefficient, and porosity from their images acquired through various scanning methods. Additionally, this article incorporates proprietary data, specifically images from four carbonate samples. Convolutional neural networks were examined as the method of choice.The results of this article comprise a scientific review of moderate depth regarding the effectiveness and applicability of the approach for determining important characteristics of porous media using deep machine learning methods based on sample images. In this article, we also present the results of predict-ing the open porosity of four carbonate samples based on their X-ray images using the convolutional neural network model we constructed. The conducted review has demonstrated that images (scans) of geological rock samples obtained through various scanning methods allow for the calculation of their transport properties with a high degree of accuracy using deep machine learning algorithms, and this can be achieved within a significantly short timeframe. This implies that deep machine learning can serve as a valuable alternative tool for estimating the properties of geological rock samples based on their images. The convolutional neural network model we constructed exhibited predictive capability for the porosity of three carbonate samples with a coefficient of determination ranging from 0.936 to 0.976.

Analysis of soil composition in experimental areas where scientific research is conducted

According to this hydromodule, scientifically based irrigation regimes of cotton rotation crops for hydromodule districts were developed for the conditions of mountainous and desert regions of the region. It was determined that the specific mass of the soil of the first area is slightly heavier than that of the second area. Determination of water permeability of the soil in the experimental areas was carried out in the spring of the year when the experiment began.

Inflow and outflow permeability tests in a very soft clay under low stresses

In situ inflow and outflow permeability tests with the BAT probe at Sarapuí II soft clay test site are presented. A description of the BAT permeability test is provided, discussing its advantages and shortcomings, especially in the case of very soft clays under low stresses. Pore pressures were monitored during probe installation and were found to be slightly lower than piezocone u2 pore pressures, consistent with the position of the filter. The role of filter tip saturation was investigated after the usual saturation procedure provided an unsatisfactory pore pressure response during probe installation. Results show that the vacuum saturation procedure provides adequate response during installation and increases the reliability of the coefficient of permeability determination in early measurements. Both inflow and outflow tests yielded similar results, indicating that careful execution of the test can lead to good test repeatability regardless of the loading condition. Various sequences of alternated inflow and outflow tests have yielded similar results, indicating that soil reconsolidation and filter clogging were negligible in the tests performed. Data are presented concerning the relationship between index parameters and the in situ coefficient of permeability for Sarapuí II clay, which plot outside the range of existing databases.