Mean Porosity Research Articles

Engineering Properties of Tamarind: A Comparison Between Shelled and Unshelled Tamarind

The experiment was conducted during April–June, 2024 in the department of Agricultural Process Engineering, Dr. Panjabrao Deshmukh Krishi Vidhyapeeth Akola, Maharashtra, India to determine the physical, chemical and frictional properties of shelled and unshelled tamarind. Standard methods are used to calculate all the engineering properties. Moisture content was determined by hot air oven method and the color was determined by digital colorimeter. The obtained results of the study were: the mean length, width and thickness of unshelled and shelled tamarind were 81.36 mm, 22.31 mm, 15.28 mm and 75.01 mm, 17.41 mm, 10.24 mm respectively. The mean bulk density, true density and porosity of unshelled and shelled tamarind were 370.01 kgm-3, 719.7 kg m-3, 48.39 % and 512.35 kg m-3, 912.73 kg m-3, 43.49% respectively. The mean arithmetic Mean Diameter, Geometric Mean Diameter, sphericity index, surface area of unshelled and shelled tamarind were39.65mm, 30.02mm, 0.38, 2866.80 mm2 and 34.22 mm, 23.45 mm, 0.332, 1754.24 mm2 respectively. The mean moisture content and color values of unshelled and shelled tamarind are 23.64%, L*=47.606, a*=8.944, b*=21.604 and 23.14%, L*=37.178, a*=11.22, b*=20.404 respectively. This study analyzed the critical differences between the engineering properties of unshelled and shelled tamarind fruit, providing valuable insights for optimizing the design and operation of machinery used in tamarind processing. Understanding these properties can improve handling, reduce processing losses, and enhance the efficiency of equipment used in cleaning, sorting, and packaging.

Microstructural response of coal fracture surface induced by ScCO2 injection measured with AFM

Fractures in coal serve as the principal channels for the migration of coalbed methane (CBM). The microscopic traits of coal fracture surface are of significance for evaluating reservoir permeability and directly influence the outcome of CO2 storage and displacement. To comprehend the impact of CO2 on the coal fracture surface, the alterations in the coal fracture surface before and after CO2 injection are investigated vis atomic force microscopy. As CO2 gradually transforms into a supercritical state, the fracture density and aperture on the coal fracture surface gradually escalate. The mean pore size and porosity of the coal fracture surfaces rose from 5.45 nm to 6.55 nm and from 4.66% to 6.85%, respectively. The proportion of micropores (<2 nm) gradually diminished. The proportions of mesopores (2–50 nm) and macropores (>50 nm) proportions gradually. Swelling, extraction and mineral dissolution are the predominant reasons for the alteration in the pore structure of the coal fracture surface. CO2 injection modifies the roughness and fractal characteristics of the coal fracture surface. The mean roughness Ra dropped from 6.54 nm to 4.03 nm, and the fractal dimension Ds declined from 2.45 to 2.28. With the fixed scanning range, the injection of CO2 has been shown to reduce the roughness of coal fracture surface and lower their fractal dimension, thereby has a positive influencing permeability enhancement. Therefore, in CO2-ECBM engineering, it is essential not only to analyze the physical properties of the target reservoir, but also to conduct a comprehensive evaluation of permeability with a suitably defined area of the reservoir.

Kinetic and thermodynamic analysis of engineered alginate–chitosan hydrogel based scaffolds for drug delivery applications

The synthesis of stimulus–responsive hydrogel–based scaffolds has been extensively investigated for controlled drug delivery applications. This study focused on synthesizing alginate and chitosan–based scaffolds for potential use in releasing antibiotic antimycotic solution (AAS) drugs. The controlled release of AAS from AAS–loaded alginate–chitosan scaffolds was investigated under distinct temperatures viz. 37 °C, 25 °C, and 10 °C, labeled as scaffolds A, B, and C, respectively. Porosity assessment revealed consistent and substantial mean porosity percentage of 95.06 ± 2.01 % across all scaffolds. The lower temperature of 10 °C significantly contributed to a gradual and consistent cumulative release of 91.67 ± 1.47 %, compared to 37 °C (94.07 ± 1.89 %) and 25 °C (92.75 ± 1.51 %). The Korsmeyer–Peppas model exhibited high R2 values (0.98, 0.97 to 0.99) for scaffolds A, B, and C, indicating its suitability for describing the in–vitro release of AAS. Furthermore, the obtained release exponent values (0.60, 0.65, and 0.72 for scaffolds A, B, and C, respectively) suggest non–Fickian diffusion as the primary mechanism governing drug release. The release was also pH–dependent, with slower release at acidic (pH 3) and faster release under basic conditions (pH 8) due to varying swelling ratios. Evaluation of thermodynamic parameters viz. Ea, ΔG, ΔH and ΔS, using the rate constant of the Korsmeyer–Peppas model, revealed positive values of ΔH > 0 and ΔS > 0, indicating the prevalence of hydrophobic interactions in the release process.

Light Scattering From High‐Porosity 3D Simulants of the Lunar Regolith at Small Phase Angles

AbstractLunar regolith consists of unconsolidated grains with high porosity, called the fairy castle structure. It is closely linked to the lunar opposition effect, which is the effect where brightness sharply increases as the phase angle approaches 0. However, owing to the Earth's gravity, it is difficult to reproduce the structure to study the physical characteristics of the lunar fairy castle structure in the laboratory. We designed a lunar fairy castle structure model for 3D printing. These models had high porosity and were simplified to tree‐like shapes. Various porous conditions of the surface were considered, represented by the number of trees, maximum trunk length, and maximum branch angle. In this study, a laboratory experiment was conducted to measure the reflectance of simulants with a fairy castle structure within a small phase angle range from 1.4 to 5.0. The result is analyzed for the sample porosity with the tangential slope of the reflectance S, which denotes the strength of the opposition effect. In addition, the results of this study were compared with lunar observation data. The porous samples exhibited a relatively large S value. The influence of branch length and attachment angle was very weak in this study. Samples with a porosity between 0.78 and 0.82 represent the similar S values to the lunar observation data, a mean porosity of lunar regolith. In conclusion, our findings suggest a potential correlation between porosity and the opposition effect in printed samples, proposing a new research approach for understanding the lunar opposition effect.

Evaluation of Additives on the Cell Metabolic Activity of New PHB/PLA-Based Formulations by Means of Material Extrusion 3D Printing for Scaffold Applications

In this study, specific additives were incorporated in polyhydroxyalcanoate (PHB) and polylactic acid (PLA) blend to improve its compatibility, and so enhance the cell metabolic activity of scaffolds for tissue engineering. The formulations were manufactured through material extrusion (MEX) additive manufacturing (AM) technology. As additives, petroleum-based poly(ethylene) with glicidyl metacrylate (EGM) and methyl acrylate-co-glycidyl methacrylate (EMAG); poly(styrene-co-maleic anhydride) copolymer (Xibond); and bio-based epoxidized linseed oil (ELO) were used. On one hand, standard geometries manufactured were assessed to evaluate the compatibilizing effect. The additives improved the compatibility of PHB/PLA blend, highlighting the effect of EMAG and ELO in ductile properties. The processability was also enhanced for the decrease in melt temperature as well as the improvement of thermal stability. On the other hand, manufactured scaffolds were evaluated for the purpose of bone regeneration. The mean pore size and porosity exhibited values between 675 and 718 μm and 50 and 53%, respectively. According to the results, the compression stress was higher (11–13 MPa) than the required for trabecular bones (5–10 MPa). The best results in cell metabolic activity were obtained by incorporating ELO and Xibond due to the decrease in water contact angle, showing a stable cell attachment after 7 days of culture as observed in SEM.

Mineral trioxide aggregate obturation quality with two obturation techniques in severe curved root canals – a micro-CT study

BackgroundThe existence of voids within the mineral trioxide aggregate (MTA) composition is one of the factors that can influence the treatment outcome. The primary objective of this study was to quantitatively assess and compare the MTA orthograde obturation quality in severe curved root canals using two different MTA compaction techniques: manual compaction with K-file, or Auger technique using micro-computed tomography (micro-CT) imaging.MethodsFor this study, 26 mandibular first molar teeth with severely curved mesiobuccal root canals were selected. These samples were randomly divided into two groups. All root canals were instrumented using ProTaper Gold rotary files up to the F3 file at the working length. In one group, OrthoMTA was compacted using a stainless steel K-file, while in the other group, the Auger technique was employed for compaction into the root canals. Once the MTA had completely set, the filled root canals were subjected to scanning using a high-resolution micro-CT scanner. The porosity volume was determined as a percentage in relation to the overal volume of the canal, and the collected data were subjected to analysis using SPSS software, with the significance level set at P < 0.05.ResultsThe two techniques had no significant difference in open, closed, and total mean porosity. In both groups, the mean of open porosity was significantly more than closed porosity.ConclusionsAccording to the results of the present study, neither of these two techniques is preferred to the other, and factors such as working time, etc., can be considered to choose the more appropriate clinical technique.

Quantification of the effect of fracturing on heterogeneity and reservoir quality of deep-water carbonate reservoirs

The Shiranish Formation represents one of the most important fractured reservoirs in northern Iraq. In this work, the petrophysical properties of the formation have been fully characterised using microscopy, core analysis, and well log analysis using conventional methods as well as new quantitative diagenetic approaches. During this work we have developed methods to quantify a petrophysical heterogeneity index (χ), reservoir quality indicator (RQI), and fracture effect index (FEI) for each of the stratigraphic units of the formation. The FEI was calculated by dividing the difference between the mean permeability of the wireline log data and the mean permeability of the unfractured core plug samples by the difference between the mean porosity of the wireline log data and the mean porosity of the unfractured core plug samples. This study shows that the Shiranish Formation has a fracturing pore system in all the characterised units, but it is particularly well developed in U.4, which shows the best reservoir quality (A and B). The new methods developed in this study can be applied to any carbonate formation to provide a trustworthy way to obtain a reservoir quality indicator linked to the petrophysical heterogeneity of the studied formation.

Process for integrating multiple porous silicon membranes with variable characteristics into planar microfluidics

We present a fabrication process based on selective ion implantation to monolithically integrate several porous silicon membranes with different morphologies in the same planar fluidic chip through a single anodization step. By manipulating the dopant concentration of specific zones of a silicon on insulator wafer, the porous silicon elements formed through electrochemical anodization present different characteristics in terms of pore size and porosity. Using this technique, we are able to fabricate both lateral porous silicon membranes and standard porous silicon membranes with vertical pores that can be used in flow-through and flow-over configurations. Achieved mean pore sizes and porosities for the various membranes integrated in the same chip range from 25 nm to 50 nm, and 65–90 %, respectively. Because porous silicon membranes have been used for biosensing and for sample preparation in microfluidics devices, this method is foreseen to enable the use of porous silicon membranes to achieve all the functions involved in the analytical process on a single chip.

Melt Pool characteristics on surface roughness and printability of 316L stainless steel in laser powder bed fusion

Purpose Surface quality and porosity significantly influence the structural and functional properties of the final product. This study aims to establish and explain the underlying relationships among processing parameters, top surface roughness and porosity level in additively manufactured 316L stainless steel. Design/methodology/approach A systematic variation of printing process parameters was conducted to print cubic samples based on laser power, speed and their combinations of energy density. Melt pool morphologies and dimensions, surface roughness quantified by arithmetic mean height (Sa) and porosity levels were characterized via optical confocal microscopy. Findings The study reveals that the laser power required to achieve optimal top surface quality increases with the volumetric energy density (VED) levels. A smooth top surface (Sa &lt; 15 µm) or a rough surface with humps at high VEDs (VED &gt; 133.3 J/mm3) can serve as indicators for fully dense bulk samples, while rough top surfaces resulting from melt pool discontinuity correlate with high porosity levels. Under insufficient VED, melt pool discontinuity dominates the top surface. At high VEDs, surface quality improves with increased power as mitigation of melt pool discontinuity, followed by the deterioration with hump formation. Originality/value This study reveals and summarizes the formation mechanism of dominant features on top surface features and offers a potential method to predict the porosity by observing the top surface features with consideration of processing conditions.

Simultaneous enhanced antibiotic pollutants removal and sustained permeability of the membrane involving CoFe2O4/MoS2 catalyst initiated with simple H2O2 backwashing

Membranes for wastewater treatment should ideally exhibit sustainable high permeate production, enhanced pollutant removal, and intrinsic physical rejection. In this study, CoFe2O4/MoS2 serves as a non-homogeneous phase catalyst; it is combined with polyether sulfone membranes via liquid-induced phase separation to simultaneously sustain membrane permeability and enhance antibiotic pollutant degradation. The prepared catalytic membranes have higher pure water flux (329.34 L m−2 h−1) than pristine polyethersulfone membranes (219.03 L m−2 h−1), as well as higher mean pore size, porosity, and hydrophilicity. Under a moderate transmembrane pressure (0.05 MPa), tetracycline (TC) in synthetic and real wastewater was degraded by the optimal catalytic membrane by 72.7 % and 91.2 %, respectively. Owing to the generation of the reactive oxygen species (ROS) during the Fenton-like reaction process, the catalytic membrane could exclude the natural organics during the H2O2 backwash step and selectively promote fouling degradation in the membrane channel. The irreversible fouling ratio of the catalyzed membrane was significantly reduced, and the flux recovery rate increased by up to 91.6 %. A potential catalytic mechanism and TC degradation pathways were proposed. This study offers valuable insights for designing catalytic membranes with enhanced filtration performance.

“Hexacelsian slurry development for 2D woven alumina fiber impregnation in CMC fabrication”

The rheological properties of BAS (BaAl2Si2O8) slurries are investigated in order to optimize the impregnation of an alumina preform to manufacture oxide/oxide composite materials. The fiber preform morphology has been deeply investigated, especially the fiber to fiber gap within tows and compared to the grain size of the matrix powder. The slurry viscosity is measured as a function of powder and organic additives concentration to find the best combination. The optimal combination is evaluated by different measurements including: zeta potential, sedimentation and wettability to verify the slurry behavior for the fibers infiltration. An aqueous slurry containing 20–25 vol% of BAS with 1 wt% of dispersing agent (Darvan 821-A™) improved the rheological properties for fibers infiltration. Finally, characterizations of the composite show a good infiltration in the fiber tows spaces and indicate a mean porosity of 37 vol%, including 9 vol% of macroporosity.

The interplay of detrital modes and depositional facies on diagenesis and petrophysics of deep-marine Miocene sandstones (Cilento Group), Southern Apennines, Italy

The Cilento Group (Langhian-to-Tortonian) is a thick turbiditic succession of the Southern Apennines foreland region that unconformably overlain the Lucanian oceanic terranes. The San Mauro Formation (SMF) form the uppermost portions of the Cilento Group, and consists of 1400–1600 m thick turbiditic succession including quartzolithic, volcanolithic, and quartzofeldspathic sandstones with several carbonatoclastic layers interbedded, passing upward from distal-to proximal-facies associations. Here, based on the vertical changes of texture and petrology in the succession, the SMF was divided in two main sections. The key depositional features and the main post-depositional processes, of lower- and upper-part of SMF, are compared with the most significant petrophysical properties with the purpose to elucidate the major controls on the porosity and permeability evolution during burial. With this aim, fifty-four thin sections were petrographically investigated, while mercury intrusion analysis was performed on twenty-four samples. Compaction, cementation, dissolution and fracturing occurred in the SMF, altering porosity and permeability. The main authigenic minerals are: 1) carbonates, mainly calcite and less dolomite, dominantly occurring as replacement of framework grains; 2) Phyllosilicates, mainly developing in the upper part of SMF as pore-filling cement or as small and incomplete grain coatings; 3) Fe-oxides occurring as coatings or localized crystals. The relationship between the compactional porosity loss (COPL) and the cementational porosity loss (CEPL) testifies the primary role of compaction in decreasing porosity, reducing the intergranular volume (IGV) to 11.1% in the lower SMF and to 16.7 % in the upper SMF. The coarse upper SMF samples exhibit lower mean porosity and permeability (6 % and 215 mD, respectively) than the fine lower SMF samples (9.2 % and 774.2 mD, respectively). In the upper section of SMF, a comparatively more widespread pore-filling cementation and the abundant detrital matrix affect depositional intergranular porosity, reducing the pore size and interconnectivity. Moreover, the higher amount of rigid grains (petrofacies dependent) and their brittle deformation produce an intricate fragmentation and micro-fracturing system, altering pores geometry and affecting permeability. On the contrary in the lower SMF, ductile components suffer compaction more than rigid ones, leading the lowest IGV. In addition, a higher volume of authigenic carbonates occur as replacement on framework components, hence playing a minor occluding role and less affecting the pore system. Composition and tectonics rule the effects of diagenetic processes in the San Mauro turbiditic succession, following the vertical evolution of depositional facies association and petrology.

Oil saturation quantitative evaluation in lacustrine shale: Novel insights from NMR T1-T2 and displacement experiments

Oil saturation is important for shale reservior to identify favorable sections and determine the geological sweet spots. Current oil saturation evaluation methods, including experiments and empirical formulas, are not suitable for shale reservoir because of the complex mineral, fluid components and pore structure characteristics. A novel method was proposed to accurately calculate the shale oil saturation through the morphological dynamic variation characteristics of the 1D NMR T2 spectra and the signal intensity of the different hydrocarbon-bearing components of the 2D NMR T1-T2 map of shale samples with different oil and water saturation The results (1) indicated that the NMR T2 spectrum revealed that the pore structure of shale samples is complex and highly heterogeneous, and the primary factor that determines the volume of displaced oil in the displacement experiment with slight differences in wettability is the shale’s pore size distribution. (2) shown that the NMR T1-T2 map serves as a useful tool in distinguishing different hydrocarbon-bearing components of shale samples, including kerogen, adsorbed oil, free oil, structural, adsorbed water, and free water. Typically, kerogen is found in the top left region of the T1-T2 map with 10 < T1 < 100 ms & 0.02 < T2 < 0.2 ms. Based on this, T2 threshold for free oil and adsorbed oil are 2 and 0.2 ms, and the corresponding threshold of pore radius are 40 and 4 nm according to the NMR theory. (3) found that the morphological characteristics of 1D NMR T2 spectra vary with the variation of shale oil saturation. Specifically, T2 geometric mean (T2gm) and interval porosity corresponding to the first peak (Ap1) are positively and negatively correlated with oil saturation respectively. Then, oil saturation calculation method is established using the above two parameters and the Root Mean Square Error (RMSE) between the measured and calculated results is 5.85 %, which reflecting the accuracy and validity. In general, this method allows the shale oil saturation to be accurately calculated and provides basis for the determination of favorable sections and evaluation of resource of shale oil reservoir. Moreover, it also offers a new idea for the oil saturation prediction by NMR logging.

Enhancement of Filtration Performance Characteristic of Glass Fiber-Based Filter Media, Part 2: Chemical Modification with Surface-Active Treatment.

Standard glass fiber filter media were chemically modified with suitably chosen surface-active agents. The aim of these modifications was to improve the three fundamental filtration performance characteristics, namely, to increase the separation efficiency, reduce the differential pressure (∆P) and increase the dirt holding capacity (DHC). The increase in separation efficiency was considered quantitatively in terms of changes in the work of adhesion between the contaminant and the modified media substrate derived from the contact angle measurements. The experimental confirmation of this behavior was demonstrated by an improved separation efficiency especially for particles in the smaller size ranges, well below the mean porosity of the original substrate. In addition, the effect of different surface modifications, especially those of the opposite ends of the surface energy values, has clearly manifested itself in the experimental results of separation efficiency derived from the multipass evaluations. Collectively, the obtained contact angle (surface energy) and separation efficiency results are strongly indicative of a wide range of filtration performance enhancements that can be achieved through suitably chosen surface-active modification of standard substrate materials.

Ensemble of Neural Networks Utilizing Seismic Attributes for Rock‐Property Inversion With Uncertainty Estimation

AbstractSeismic inversion holds significant importance across various domains of geoscience and engineering, including the characterization of energy resource reservoirs, the assessment of polluted sites, and CO2 storage. It is a process of estimating rock properties from seismic data that is inherently uncertain, nonlinear, non‐unique, and highly challenging. Using multiple seismic attributes increases the size of the data, requiring considerable processing resources and time. However, deep learning can accurately fit quantities of nonlinear variables, making it an excellent method for predicting spatially distributed subsurface properties. We trained some multi‐output regression neural networks to carry out porosity inversion from seismic data. We initially computed a series of seismic attributes and generated the corresponding porosity using interpreted horizons, well logs, and seismic data. Subsequently, we proposed a technique to identify the most relevant seismic attributes for porosity inversion. Because our networks work as stochastic modeling entities, we created a weight‐averaging ensemble approach to build a strong model with the highest level of accuracy. We combined realizations from baseline entities, considering their respective performance levels. Using the statistics between these realizations and the robust model, we determined the degree of uncertainty associated with the outcome. We found an R2 of 0.993 and an MAE of 0.00112 in the F3 block offshore the Netherlands, proving the method's effectiveness. The mean porosity was 0.175193, compared to 0.175626 from a reference model, and the mean uncertainty was ±0.0008998.

Gravimetric characteristics and friction parameters of common bean (Phaseolus vulgaris L.)

When designing appropriate machinery systems, equipment, and infrastructures for interacting with, cultivating, gathering, and agriculture-related processing, it is required to have an understanding of the engineering characteristics of agricultural products. This unpredictability makes it difficult to design or develop machines that can efficiently and effectively manage a wide range of product characteristics. Experimental analysis was used to accomplish the study's objective, which was to investigate the implications of variation on the gravimetric characteristics and frictional parameters of common bean (Phaseolus vulgaris L.) concerning the design of the threshing machine. The mean average values of gravimetric parameters were determined by analysing the experimental data: arithmetic mean diameter (7.042 ± 0.473 mm), geometric diameter (6.737 ± 0.463 mm), bulk density (781.20 ± 25.34 kg m-3), true density (1347.03 ± 143.0 kg m-3), porosity (41.385 ± 7.05%), width (6.316 ± 0.502 mm), thickness (4.962 ± 0.50 mm), projected area (49.194 ± 6.715 mm2), and volume of the seed (161.689 ± 3.778 mm3). The average moisture content values were found to be 11.214±1.185% on a dry basis, the static coefficient of friction varied between 0.276 and 0.386 on the surface of iron sheets, 0.294 to 0.435 on stainless steel, 0.317 to 0.434 on galvanized iron, 0.321 to 0.451 on medium density fiberboard, 0.319 to 0.480 on aluminum, 0.310 to 0.470 on painted sheets, 0.320 to 0.440 on glass, 0.333 to 0.447 on plastic, and 0.374 to 0.575 on rubber. Perforated sheet surfaces showed the highest static coefficients of friction, followed by rubber, plastic, plywood, glass, aluminum, galvanized iron, painted sheet, stainless steel, and iron sheet surfaces. These data are not only required for predicting loads in agricultural storage structures but are also needed to establish useful sources for the development of machinery for handling, cleaning, storing, transporting and drying, among other things.

A new method for investigating the impact of temperature on in-situ reservoir properties using high-temperature AFM

Accurately evaluating the influence of temperature variations is crucial for geothermal engineering. Existing conventional testing methods are limited in providing detailed characterizations of reservoir micro properties at high temperatures. This study employed variable-temperature AFM testing techniques to examine sandstone and limestone under in-situ temperatures (25-200°C). The study analyzed the mechanisms behind the temperature effects on rock properties and established theoretical models for porosity and permeability variations with elevated temperatures based on these mechanisms. The research revealed that sandstone and limestone exhibit similar temperature effects at high temperatures. The pore fractal dimension of sandstone and limestone does not change with temperature change. As the temperature increases, sandstone and limestone experience mean roughness (Ra) and porosity reductions. The impact of high temperature was more pronounced on sandstone compared to limestone, with sandstone showing a decrease of 2.8 % and 0.59 % in mean roughness (Ra) and AFM porosity, respectively, from 25 °C to 200 °C, while limestone exhibited reductions of 1.4 % and 0.085 %, respectively. With increasing temperature, sandstone transformed some pores with equivalent diameters of 1-2.5 μm to pores smaller than 1μm, while limestone did not show significant changes in pore structure. The temperature effects on sandstone and limestone were attributed to mineral expansion. Sandstone contains a higher proportion of minerals with a high coefficient of thermal expansion, such as quartz. In contrast, limestone primarily comprises minerals with lower thermal expansion coefficients, such as calcite, resulting in a more significant temperature impact on sandstone than on limestone. The theoretical models based on the mechanisms for porosity and permeability at high temperatures exhibited good predictive performance for sandstone and are more suitable for reservoirs predominantly composed of minerals with high coefficients of thermal expansion. The variation of porosity and permeability at high temperatures have different impacts on geothermal reservoirs. Temperature effects on porosity and permeability should be considered in geothermal engineering.

New Methods in Digital Wood Anatomy: The Use of Pixel-Contrast Densitometry with Example of Angiosperm Shrubs in Southern Siberia.

This methodological study describes the adaptation of a new method in digital wood anatomy, pixel-contrast densitometry, for angiosperm species. The new method was tested on eight species of shrubs and small trees in Southern Siberia, whose wood structure varies from ring-porous to diffuse-porous, with different spatial organizations of vessels. A two-step transformation of wood cross-section photographs by smoothing and Otsu's classification algorithm was proposed to separate images into cell wall areas and empty spaces within (lumen) and between cells. Good synchronicity between measurements within the ring allowed us to create profiles of wood porosity (proportion of empty spaces) describing the growth ring structure and capturing inter-annual differences between rings. For longer-lived species, 14-32-year series from at least ten specimens were measured. Their analysis revealed that maximum (for all wood types), mean, and minimum porosity (for diffuse-porous wood) in the ring have common external signals, mostly independent of ring width, i.e., they can be used as ecological indicators. Further research directions include a comparison of this method with other approaches in densitometry, clarification of sample processing, and the extraction of ecologically meaningful data from wood structures.

Developing deep learning methods for pre-stack seismic data inversion

Inversion of pre-stack seismic data is important for building accurate models of hydrocarbon reservoirs used to estimate reserves and set up efficient production strategies. Conventional methods often involve challenging procedures. The limited bandwidth, noisy nature, and fact that the pre-stack seismic data has more than one component all affect how accurate and stable the inversion solution is. Deep learning (DL) is a cost-effective and accurate method for predicting spatially distributed properties. We utilized specific deep-learning algorithms to create a methodology for estimating porosity based on angle gathers. The workflow involved trace editing for amplitude variation compensation, noise reduction, and organizing data into appropriate common depth point (CDP) gathers. Well-logging data and approved seismic horizons were utilized to obtain the corresponding CDP gather’ porosity labels. From initial CDP gathers, we computed a series of seismic attributes and developed an efficient technique to identify the most relevant ones that we utilized to train base models. We explored different hyper-parameters to determine the optimal characteristics for the method's objective function. We subsequently developed an integration approach that assigns appropriate weights to aggregate individual base models to create a robust model. We developed a statistical analysis method to determine the confidence level in the final prediction. In real-world scenarios, the new methodology outperformed conventional and popular DL inversion approaches, with an R2 of 0.989 compared to 0.954 and 0.967, a mean porosity of 0.174868 compared to 0.174985, and a mean uncertainty of ±0.000714 at the well location.

Enhancing predictions of remedial reagent transport via a vertical groundwater circulation well with high-resolution aquifer characterization

The vertical groundwater circulation well (GCW) is a commonly used technique in contaminated sites to remove secondary contaminants from low permeable zones. Early GCW studies often used simple subsurface hydraulic properties, such as anisotropic homogeneous aquifers or low conductivity lens/blocks, to mimic the complex subsurface heterogeneity. Although studies based on simplified representations of aquifer heterogeneity provide straightforward flow and transport information for engineering design of a GCW, they may over- or under-estimate contaminant fate and transport in the field. The objective of this study is to identify key heterogeneity factors that control the capture zone extension and to examine the extent to which the accuracy of estimated heterogeneity spatial distributions influences the prediction of remedial reagent transport. To achieve these objectives, we utilized Monte Carlo simulation to investigate the extension of the circulation zone in heterogeneous aquifers and to identify the key factors that contribute most to the variability of the circulation zone. Three commonly used geostatistical approaches (equivalent homogeneous, kriging, and highly parameterized methods) were employed to estimate the spatial distributions of key factors. The reliabilities of these estimated fields were evaluated through their remedial reagent transport predictability. The key factor analysis revealed that the mean porosity value, the variance of lnK, and the correlation length of lnK profoundly influence the lateral expansion of the capture zone. Neglecting the aquifer hydraulic conductivity heterogeneity underestimates the extension of the circulation zone and the spread of remedial reagent. Additionally, utilizing a highly parameterized approach to estimate the high-resolution K field can accurately reproduce the key remedial reagent distributions. The concentration arrival time and peak concentration are significantly improved compared to those predictions based on the equivalent homogeneous and kriged K fields.