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Experimental Study and Analysis of Matrix Acidizing for Mishrif Formation-Ahdeb Oil Field
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Carbonate matrix stimulation technology has progressed tremendously in the last decade through creative laboratory research and novel fluid advancements. Still, existing methods for optimizing the stimulation of wells in vast carbonate reservoirs are inadequate. Consequently, oil and gas wells are stimulated routinely to expand production and maximize recovery. Matrix acidizing is extensively used because of its low cost and ability to restore the original productivity of damaged wells and provide additional production capacity. The Ahdeb oil field lacks studies in matrix acidizing; therefore, this work provided new information on limestone acidizing in the Mishrif reservoir. Moreover, several reports have been issued on the difficulties encountered during the stimulation operation of the Ahdeb oil field, particularly for the development of the Mishrif reservoir. Since the new core flooding system is built to operate safely and straightforwardly. This study introduced the results of Matrix acidizing experiments, covering the most recent developments in linear core flooding. High-permeability flow pathways are created, and a longer and wider wormhole was generated at a high acid injection rate (6.67 cc/min). The acid efficiency curve yielded the lowest pore volume injected at the breakthrough of the PV_(bt-opt) is 2.73 and the v_(i-opt)=0.6 cm/min; thus, the optimum injection rate that results in an optimal possible wormhole and the least quantity of acid being used for this reservoir is 2.16 cc/min. This research evaluated the impact of matrix acidizing treatment on acoustic characteristics, which studies show are lacking or have never been investigated previously. Furthermore, in the assessment of geomechanical rock properties and elastic and petrophysical parameters before and after acid injection, one of the new concepts discovered during the lab experiment observation of the acoustic waveform before and after acid treatment for the tested rock sample is that the initial arrival time before acid treatment is 21.6 microseconds, with a delay of 31.2 microseconds attributed to the wormhole channel and mineral disintegration. CT-Scan applications in matrix acidizing were investigated in this research; additionally, a 3D view of plug samples was constructed to represent the wormhole extension via CT-processing software. A license of Stimpro Stimulation Software has been used to validate the experimental work to the field scale, making it the most comprehensive instrument for planning and monitoring matrix acid treatment and utilizing actual data to provide a far better knowledge of the well's reaction, with methods that represent the reality of what is happening in the reservoir before, during, and after matrix acid treatments, through the post-treatment skin factor which is the most often utilized statistic for analyzing stimulation treatments and relies on the geometry of the wormholed zone. The acid treatment evaluated for the well AD-12, primarily for the zone Mi4; matrix acid treatments can have their production behavior predicted or matched using the reservoir simulation and production analysis option, employing the numerical simulation license software Petrel (Schlumberger) and Rubis (KAPPA) to determine the efficacy of previous treatments and the economics associated with future treatments. The estimated oil gain volume and percentage for the Mi4 unit in Ad-12 using particularly skin value -3.97 computed from Stimpro software for real stimulation acid job, it is yield enhancement in production of oil gain volume 6154 barrels as well as 105% increase of gain percentage for three months after matrix acidizing.

Publication Date
Sat May 24 2025
Journal Name
Iraqi Journal For Computer Science And Mathematics
Intrusion Detection System for IoT Based on Modified Random Forest Algorithm
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An intrusion detection system (IDS) is key to having a comprehensive cybersecurity solution against any attack, and artificial intelligence techniques have been combined with all the features of the IoT to improve security. In response to this, in this research, an IDS technique driven by a modified random forest algorithm has been formulated to improve the system for IoT. To this end, the target is made as one-hot encoding, bootstrapping with less redundancy, adding a hybrid features selection method into the random forest algorithm, and modifying the ranking stage in the random forest algorithm. Furthermore, three datasets have been used in this research, IoTID20, UNSW-NB15, and IoT-23. The results are compared with the three datasets men

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Publication Date
Mon Dec 05 2022
Journal Name
Baghdad Science Journal
MSRD-Unet: Multiscale Residual Dilated U-Net for Medical Image Segmentation
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Semantic segmentation is an exciting research topic in medical image analysis because it aims to detect objects in medical images. In recent years, approaches based on deep learning have shown a more reliable performance than traditional approaches in medical image segmentation. The U-Net network is one of the most successful end-to-end convolutional neural networks (CNNs) presented for medical image segmentation. This paper proposes a multiscale Residual Dilated convolution neural network (MSRD-UNet) based on U-Net. MSRD-UNet replaced the traditional convolution block with a novel deeper block that fuses multi-layer features using dilated and residual convolution. In addition, the squeeze and execution attention mechanism (SE) and the s

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Publication Date
Sat Jan 01 2022
Journal Name
Proceeding Of The 1st International Conference On Advanced Research In Pure And Applied Science (icarpas2021): Third Annual Conference Of Al-muthanna University/college Of Science
Efficient approach for solving high order (2+1)D-differential equation
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Publication Date
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
Perceptually Important Points-Based Data Aggregation Method for Wireless Sensor Networks
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The transmitting and receiving of data consume the most resources in Wireless Sensor Networks (WSNs). The energy supplied by the battery is the most important resource impacting WSN's lifespan in the sensor node. Therefore, because sensor nodes run from their limited battery, energy-saving is necessary. Data aggregation can be defined as a procedure applied for the elimination of redundant transmissions, and it provides fused information to the base stations, which in turn improves the energy effectiveness and increases the lifespan of energy-constrained WSNs. In this paper, a Perceptually Important Points Based Data Aggregation (PIP-DA) method for Wireless Sensor Networks is suggested to reduce redundant data before sending them to the

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
An Effective Hybrid Deep Neural Network for Arabic Fake News Detection
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Recently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural

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Publication Date
Mon Jul 15 2019
Journal Name
Iet Microwaves, Antennas & Propagation
Hilbert metamaterial printed antenna based on organic substrates for energy harvesting
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Abstract In this study, an investigation is conducted to realise the possibility of organic materials use in radio frequency (RF) electronics for RF-energy harvesting. Iraqi palm tree remnants mixed with nickel oxide nanoparticles hosted in polyethylene, INP substrates, is proposed for this study. Moreover, a metamaterial (MTM) antenna is printed on the created INP substrate of 0.8 mm thickness using silver nanoparticles conductive ink. The fabricated antenna performances are instigated numerically than validated experimentally in terms of S11 spectra and radiation patterns. It is found that the proposed antenna shows an ultra-wide band matching bandwidth to cover the frequencies from 2.4 to 10 GHz with bore-sight gain variation from 2.2 to

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
AlexNet-Based Feature Extraction for Cassava Classification: A Machine Learning Approach
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Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has

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Scopus (9)
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Publication Date
Sat May 18 2024
Journal Name
Proximus Journal Of Sports Science And Physical Education
STUDYING THE REALITY OF ADMINISTRATIVE PROBLEMS FOR MEMBERS OF THE ADMINISTRATIVE BODIES OF FIRST-CLASS FOOTBALL CLUBS FROM THE PLAYERS’ POINT OF VIEW
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The research aims to study the administrative problems in the sports management of the members of the administrative bodies of the first-class clubs of the province of Baghdad in football. The researchers used the descriptive approach (survey study) for its relevance to the nature of the research. The research community is represented by first-class football players, who numbered (176) players. The research sample was chosen by the deliberate method, as the basic research sample reached (136) individuals from the total research community. The researchers used the questionnaire to collect the necessary data to achieve the goal of the research by applying a questionnaire that aims to ident

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Publication Date
Sun Sep 01 2013
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Impact of applying the third of basel committee11 conventions(market disciplin) in the efficient of significance components for factors of banking capital risks
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We have focused the research problem through an assessment of the applicability of the third pillar of the decisions of the Basel Committee 11 (market discipline) or not and its impact on both the adequacy of bank capital, supervisory oversight and banking risks and the statement weaknesses commitment banking institutions and which in turn lead to the stability of the financial system as a whole.                         .
The research is important statement on the importance of big capital in the banking business and the attributes of a role in the absorption of losses suffered by the bank, which reflects the willin

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Publication Date
Wed Dec 28 2022
Journal Name
Al–bahith Al–a'alami
Contents of Campaign Advertisements “Take the Vaccine . to Protect Yourself” to Raise Awareness about Vaccines Against صthe Covid-19 Virus (Analytical Study of the Ministry of Health Facebook Page)
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        This paper aims to identify the contents of the advertisements of the (Take the Vaccine .. to Protect Yourself) campaign that was carried out by the Iraqi Ministry of Health for the period from (11/19/2020) to (4/1/2022), to raise awareness of the anti-Covid 19 virus vaccines, which it published on its official page on Facebook. The researcher used a comprehensive inventory method for the research community, and used the content analysis tool.                                                                             

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