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Effect of acid treatment on the geomechanical properties of rocks: an experimental investigation in Ahdeb oil field

Acidizing is one of the most used stimulation techniques in the petroleum industry. Several reports have been issued on the difficulties encountered during the stimulation operation of the Ahdeb oil field, particularly in the development of the Mishrif reservoir, including the following: (1) high injection pressures make it difficult to inject acid into the reservoir formation, and (2) only a few acid jobs have been effective in Ahdeb oil wells, while the bulk of the others has been unsuccessful. The significant failure rate of oil well stimulation in this deposit necessitates more investigations. Thus, we carried out this experimental study to systematically investigate the influence of acid treatment on the geomechanical properties of Mi4 formation of the Mishrif reservoir. The acid core-flood experiments were performed on seven core samples from the oil reservoir in central Iraq. The porosity, permeability, acoustic velocities, rock strength, and dynamic elastic parameters were computed before and after the acidizing treatment. To determine the optimal acid injection rate, different injection flow rates were used in the core-flooding experiments. The propagation of an acid-induced wormhole and its effect on the rock properties were analyzed and compared to that of intact rocks. Computed tomography (CT) scan and a 3D reconstruction technique were also conducted to establish the size and geometry of the generated wormhole. To analyze the influence of mineralogical variation and heterogeneity and confirm the consistency of the outcomes, acidizing experiments on different rock samples were conducted. The results demonstrate that for all the rock samples studied, the mechanical properties exhibit rock weakening post-acid treatment. The Young’s modulus reduced by 26% to 37%, while the Poisson’s ratio, the coefficient of lateral earth pressure at rest, and the material index increased by 13% to 20%, 23% to 32%, and 28% to 125%, respectively. The CT scan visually confirmed that the acid treatment effectively creates a pathway for fluid flow through the core.

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Publication Date
Thu Sep 26 2019
Journal Name
International Journal Of Pharmaceutical Research
Synthesis and identification of novel 2-thioxoimidazolidin- 4-one derivatives containing azo and ester groups

The compounds 3-[4̄-(4˭-methoxybenzoyloxy) benzylideneamino]-2-thioxo-imidazolidine-4-one(3)aand 4-(1-(5-oxo- 2-thioxoimidazolidin-1-ylimino)ethyl)phenyl acetate(3)b were prepared from the reaction of aromatic aldehyde or ketone(1)a,bwith thiosemicarbazide to give aryl thiosemicarbazones(2)a,b ,followed by cyclization with ethylchloroacetate in the presence of fused sodium acetate. Treatment the compounds(3)a,bwith 4- hydroxybenzenediazoniumchloride yielded the correspondings4-((4-((4-hydroxyphenyl)diazenyl)-5-oxo-2- thioxoimidazolidin-1-ylimino)methyl)phenyl 4-methoxybenzoate(4)aand4-(1-(4-((4-hydroxyphenyl)diazenyl)-5-oxo-2- thioxoimidazolidin-1-ylimino)ethyl)phenyl acetate(4)b.The new 2-thioxo-imidazolidin-4-one with esters (5-7)a,b sy

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Publication Date
Tue Dec 22 1998
Journal Name
College Of Education Ibn Rushd
Investigating Iraqi College students' production of English Intra Word and Inter Word Consonant Clusters

MR Younus, 1998

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Publication Date
Sat Apr 30 2022
Journal Name
Eastern-european Journal Of Enterprise Technologies
Improvement of noisy images filtered by bilateral process using a multi-scale context aggregation network

Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d

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Publication Date
Thu May 28 2020
Journal Name
Journal Of Generic Medicines: The Business Journal For The Generic Medicines Sector
Determinants of national drug products acceptance across patients, pharmacists, and manufacturers: A mixed method study
Introduction

The national pharmaceutical industry is pivotal for both the health sector and the national economy. This study aims to identify determinants of national drug products acceptance. The objectives of this study were to quantitatively measure the level of patient and community pharmacist acceptance of national drug products available in community pharmacies and to qualitatively explore the barriers facing national pharmaceutical companies and investigate the suggested solutions.

Methods

This cross-sectional study used an explanatory mixed method design. It was conducted in Baghdad, Iraq from July through October 2018. The stud

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Publication Date
Thu Feb 01 2024
Journal Name
Russian Journal Of Bioorganic Chemistry
Synthesis, Characterization of Formazan Derivatives from Isoniazid and Study Their Antioxidant Activity and Molecular Docking

Objective: Synthesis, Characterization of formazan derivatives and studies the antioxidant activity of prepared compounds and molecular docking. Methods: In this study, formazan compounds (III–XIV) were produced by combining Schiff base compounds (I), (II) with diazonium salts resulting from reactions of different aromatic amines with sodium nitrate in the presence of Con.HCl at 0–5°C. When isonicotinic acid hydrazide reacts with (N,N-dimethylbenzaldehyde, 4-hydroxy-3-methoxybenzaldehyde) in the presence glacial acetic acid as a solvent Schiff base compounds are created. Results: The prepared compounds were identified by FT-IR, 1H NMR, 13C NMR, then the antioxidant activity of the derivatives and molecular docking were studied. D

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Publication Date
Fri Jan 15 2021
Journal Name
Plant Archives
ISOLATION AND IDENTIFICATION OF GBS BACTERIA FROM MASTITIS BY CAMP TEST AND LANCEFIELD’S SEROLOGICAL GROUPING

Mastitis is an udder tissue inflammation which has infected various species of animals. It happens through several types of pathogenic bacteria, particularly Streptococcus agalactiae. GBS is a leading cause of cow mastitis. In our sample, 9.52% of Streptococcus agalactiae were isolated which were collected from bovine mastic milk and identified by biochemical tests such as catalase, oxidase, Production of indole, fermentation of sugar, an examination of antibiotic sensitivity, CAMP test and group kits of Lancefield. The results showed that all Streptococcus agalactiae isolate was diagnosed by CAMP test by the appearance of the arrowhead in blood agar and by the appearance of visible agglutination on a card in the serological grouping kit of

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Publication Date
Thu May 23 2019
Journal Name
The International Journal Of Artificial Organs
Real-time classification of shoulder girdle motions for multifunctional prosthetic hand control: A preliminary study

In every country in the world, there are a number of amputees who have been exposed to some accidents that led to the loss of their upper limbs. The aim of this study is to suggest a system for real-time classification of five classes of shoulder girdle motions for high-level upper limb amputees using a pattern recognition system. In the suggested system, the wavelet transform was utilized for feature extraction, and the extreme learning machine was used as a classifier. The system was tested on four intact-limbed subjects and one amputee, with eight channels involving five electromyography channels and three-axis accelerometer sensor. The study shows that the suggested pattern recognition system has the ability to classify the sho

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Publication Date
Sat Jan 01 2022
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science (ijeecs)
Increasing validation accuracy of a face mask detection by new deep learning model-based classification

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

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Publication Date
Mon Apr 24 2023
Journal Name
Materials Research Innovations
Surface modification of poly(methyl methacrylate)-sulphadiazine complexes as self photostabilizer against Ultraviolet (UV) Irradiation

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Publication Date
Fri Jul 01 2016
Journal Name
Tetrahedron
Novel bent-core mesogenic of 4-amino-triazole derivatives: synthesis, characterization and liquid crystalline study

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