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Evaluation of Rock Typing Methods in a Carbonate Reservoir: A Case Study of the Jeribe-Euphrates Formation in the Fauqi Oil Field, Southern Iraq
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Accurate rock typing is essential for reservoir characterization because heterogeneous carbonate reservoirs exhibit complex pore systems that weaken conventional porosity- permeability relationships. This study presents a comprehensive comparative evaluation of conventional and machine learning-based rock typing techniques for the Jeribe-Euphrates carbonate reservoir in the Fauqi Oil Field, southern Iraq. Unlike previous studies that focused on a single classification approach, this work systematically compares Hydraulic Flow Units, Discrete Rock Types, the Winland (R35) method, Lorenz curve analysis, Accumulated Correlation analysis, and machine learning clustering techniques using a unified dataset. The analysis was conducted on 179 core samples with porosity and permeability measurements. Hydraulic Flow Units, Discrete Rock Types, Winland, Lorenz, and Accumulated Correlation methods were applied to classify reservoir rocks, whereas K-means and Expectation-Maximization (EM) algorithms were used to evaluate machine learning-based rock typing. The performance of each method was quantitatively assessed using regression equations, coefficients of determination (R2), variance, standard deviation, and coefficient of variation. The results indicate a weak overall porosity-permeability relationship (R2=0.2675), confirming the pronounced heterogeneity of the studied reservoir. Among all evaluated approaches, the HFU method provided the most consistent and reliable rock classification, identifying four hydraulic flow units with the lowest statistical variability (variance = 0.017423) and the most reliable reservoir-quality characterization. Although the DRT and machine learning approaches achieved high R2 values for some individual classes, their overall classifications exhibited greater variability and lower consistency. Incorporating the Winland pore throat radius (R35) improved clustering performance but did not outperform the Hydraulic Flow Units approach. Overall, the results demonstrate that the Hydraulic Flow Units method is the most suitable approach for defining hydraulic flow units in heterogeneous carbonate reservoirs, providing a reliable framework for reservoir characterization, static geological modeling, and flow unit identification.  

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Publication Date
Thu Aug 18 2016
Journal Name
Artificial Cells, Nanomedicine, And Biotechnology
Biosynthesis of silver nanoparticles from <i>Catharanthus roseus</i> leaf extract and assessing their antioxidant, antimicrobial, and wound-healing activities
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Publication Date
Thu Mar 01 2018
Journal Name
Spectrochimica Acta Part A: Molecular And Biomolecular Spectroscopy
Application of dyes extracted from Alternanthera dentata leaves and Musa acuminata bracts as natural sensitizers for dye-sensitized solar cells
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Publication Date
Thu Nov 07 2024
Journal Name
Journal Of Thermal Analysis And Calorimetry
Performance improvement of phase change material (PCM)-based shell-and-tube-type latent heat energy storage system utilizing curved fins
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Publication Date
Tue May 12 2026
Journal Name
Canadian Metallurgical Quarterly
Investigation of Te <sub>50</sub> Se <sub>50-x</sub> Sn <sub>x</sub> alloys’ structural and electrical characteristics
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Publication Date
Tue Jun 24 2025
Journal Name
Food And Bioprocess Technology
Classification of Apple Slices Treated by Atmospheric Plasma Jet for Post-harvest Processes Using Image Processing and Convolutional Neural Networks
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Abstract<p>Apple slice grading is useful in post-harvest operations for sorting, grading, packaging, labeling, processing, storage, transportation, and meeting market demand and consumer preferences. Proper grading of apple slices can help ensure the quality, safety, and marketability of the final products, contributing to the post-harvest operations of the overall success of the apple industry. The article aims to create a convolutional neural network (CNN) model to classify images of apple slices after immersing them in atmospheric plasma at two different pressures (1 and 5 atm) and two different immersion times (3 and again 6 min) once and in filtered water based on the hardness of the slices usin</p> ... Show More
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Publication Date
Sun Jan 01 2023
Journal Name
Phyton
Toxic and Antifeedant Effects of Different Pesticidal Plant Extracts against Beet Armyworm (&lt;i&gt;Spodoptera exigua&lt;/i&gt;)
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The beet armyworm (BAW), Spodoptera exigua (Lepidoptera: Noctuidae) is a highly destructive pest of vegetables and field crops. Management of beet armyworm primarily relies on synthetic pesticides, which is threatening the beneficial community and environment. Most importantly, the BAW developed resistance to synthetic pesticides with making it difficult to manage. Therefore, alternative and environment-friendly pest management tactics are urgently required. The use of pesticidal plant extracts provides an effective way for a sustainable pest management program. To evaluate the use of pesticidal plant extracts against BAW, we selected six plant species (Lantana camara, Aloe vera, Azadirachta indica, Cymbopogon citratus, Nicotiana tabacum ,

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Publication Date
Sun Mar 06 2022
Journal Name
Nature Environment And Pollution Technology
Green Synthesis Of Bimetallic Iron/Copper Nanoparticles Using Ficus Leaves Extract For Removing Orange G(OG) Dye From Aqueous Medium
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This study shows that it is possible to fabricate and characterize green bimetallic nanoparticles using eco-friendly reduction and a capping agent, which is then used for removing the orange G dye (OG) from an aqueous solution. Characterization techniques such as scanning electron microscopy (SEM), Energy Dispersive Spectroscopy (EDAX), X-Ray diffraction (XRD), and Brunauer-Emmett-Teller (BET) were applied on the resultant bimetallic nanoparticles to ensure the size, and surface area of particles nanoparticles. The results found that the removal efficiency of OG depends on the G‑Fe/Cu‑NPs concentration (0.5-2.0 g.L-1), initial pH (2‑9), OG concentration (10-50 mg.L-1), and temperature (30-50 °C). The batch experiments showed

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Publication Date
Sat Jul 02 2016
Journal Name
Bioremediation Journal
Kinetic, thermodynamic, and equilibrium biosorption of Pb(II), Cu(II), and Ni(II) using dead mushroom biomass under batch experiment
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In this study, a low-cost biosorbent, dead mushroom biomass (DMB) granules, was used for investigating the optimum conditions of Pb(II), Cu(II), and Ni(II) biosorption from aqueous solutions. Various physicochemical parameters, such as initial metal ion concentration, equilibrium time, pH value, agitation speed, particles diameter, and adsorbent dosage, were studied. Five mathematical models describing the biosorption equilibrium and isotherm constants were tested to find the maximum uptake capacities: Langmuir, Freundlich, Redlich-Peterson, Sips, and Khan models. The best fit to the Pb(II) and Ni(II) biosorption results was obtained by Langmuir model with maximum uptake capacities of 44.67 and 29.17 mg/g for these two ions, respectively, w

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Publication Date
Thu May 15 2025
Journal Name
Chemchemtech
SYNTHESIS, CHARACTERIZATION AND SCREENING OF ANTIMICROBIAL ACTIVITY FOR SOME NEW SCHIFF BASES AND THIAZOLIDINONE DERIVATIVES DERIVED FROM AROMATIC CARBOXYLIC ACID
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In this study, the antimicrobial properties of newly synthesized Schiff bases (4a-4e) and thiazolidinone compounds (5a-5e) generated from 3,5-dinitrobenzoic acid were assessed. These compounds were obtained by reacting 3,5-dinitrobenzoic acid (1) with ethanol in a few drops of concentrated H2SO4 to produce the ester (2). The acid hydrazide (3), which was produced by treating the ester with hydrazine hydrate, reacted with the proper aldehydes, including 4-bromobenzaldehyde, 4-chlorobenzaldehyde, 4-hydroxybenzaldehyde, 4-methoxybenzaldehyde, and 4-hydroxy-3-methoxybenzaldehyde, respectively, to form Schiff bases (4a-4e). The thiazolidinone compounds (5a-5e) were produced by the cyclocondensation reaction of compounds (4a-4e) with thio

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Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Antimicrobial Effect of Eco- Friendly Silver Nanoparticles Synthesis by Iraqi Date Palm (Phoenix dactylifera) on Gram-Negative Biofilm-Forming Bacteria
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Date palm silver nanoparticles are a green synthesis method used as antibacterial agents. Today,
there is a considerable interest in it because it is safe, nontoxic, low costly and ecofriendly. Biofilm bacteria
existing in marketed local milk is at highly risk on population health and may be life-threatening as most
biofilm-forming bacteria are multidrug resistance. The goal of current study is to eradicate biofilm-forming
bacteria by alternative treatment green synthesis silver nanoparticles. The biofilm formation by bacterial
isolates was detected by Congo red method. The silver nanoparticles were prepared from date palm
(khestawy) fruit extract. The formed nanoparticles were characterized with UV-Vis

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