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Kick tolerance control during well drilling in southern Iraqi deep wells
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The importance of kick tolerance in well operations has recently increased due to its implications in well design, in drilling and well control. To study a simple method for the application of kick tolerance concept in an effective way on the basis of field data, this research purpose is to improve knowledge about Kick Tolerance and represents a technical basis for the discussion on revision of standard procedure.

   The objective of this work is to review and to present a methodology of determination the kick tolerance parameters using the circulation kicks tolerance concepts.

   The proposed method allows to know, to evaluate and to analyze the kick tolerance problem in order to make the drilling execution safer and more economical by reducing the probability to have an incident.

   The calculations of presented methodologies were based upon calculated input values such as ppore and pfrac. and not upon measured leak-off test and RFT (less accurate) input values as in traditional methods. The paper also analyses the calculations not with KT parameters only, but it has continued to give the killing operation procedure to such high pressure high temperature (HPHT) wells.

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
3D scenes semantic segmentation using deep learning based Survey
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Abstract<p>Semantic segmentation realization and understanding is a stringent task not just for computer vision but also in the researches of the sciences of earth, semantic segmentation decompose compound architectures in one elements, the most mutual object in a civil outside or inside senses must classified then reinforced with information meaning of all object, it’s a method for labeling and clustering point cloud automatically. Three dimensions natural scenes classification need a point cloud dataset to representation data format as input, many challenge appeared with working of 3d data like: little number, resolution and accurate of three Dimensional dataset . Deep learning now is the po</p> ... Show More
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Publication Date
Mon Apr 01 2019
Journal Name
Journal Of Engineering
Rehabilitation of Reinforced Concrete Deep Beam by Epoxy Resin
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This investigation presents an experimental and analytical study on the behavior of reinforced concrete deep beams before and after repair. The original beams were first loaded under two points load up to failure, then, repaired by epoxy resin and tested again. Three of the test beams contains shear reinforcement and the other two beams have no shear reinforcement. The main variable in these beams was the percentage of longitudinal steel reinforcement (0, 0.707, 1.061, and 1.414%). The main objective of this research is to investigate the possibility of restoring the full load carrying capacity of the reinforced concrete deep beam with and without shear reinforcement by using epoxy resin as the material of repair. All be

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Publication Date
Mon Jan 01 2024
Journal Name
Computers, Materials &amp; Continua
Credit Card Fraud Detection Using Improved Deep Learning Models
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Publication Date
Mon Jan 09 2023
Journal Name
2023 15th International Conference On Developments In Esystems Engineering (dese)
Deep Learning-Based Speech Enhancement Algorithm Using Charlier Transform
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Publication Date
Tue Jan 24 2023
Journal Name
Journal Of Advanced Biotechnology And Experimental Therapeutics
Influence of the high mobility group A1 genetic polymorphism on indices of metabolic syndrome and insulin resistance in the Iraqi population: Case-control study
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The high mobility group A1 gene (HMGA1) rs139876191 variant has been related to metabolic syndrome and type 2 diabetes, but data are lacking in Middle Eastern populations. The study aimed to assess whether the HMGA1 rs139876191 variant is associated with metabolic syndrome risk and whether this variant predicts the risk of insulin resistance. This case-control study was carried out at single center in Kirkuk city/ Iraq from February to August 2022. Polymorphisms in HMGA1 and genotyping were identified by Sanger sequencing of genomic DNA obtained from 91 Iraqi participants (61 patients with metabolic syndrome and 30 control). Lipid profile, serum (glucose and insulin), glycated hemoglobin, blood pressure, body mass index, and waist circumfer

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Publication Date
Fri Dec 01 2023
Journal Name
Baghdad Science Journal
Preparing New Ceramic Membranes from Syrian Zeolite Coated with Silver Nanoparticles to Treatment Wells Water
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As a result of the exacerbation of the problem of water pollution, research was directed towards studying the treatment using ceramic membranes, which proved to be highly effective in treating all water sources. The research aims to study the possibility of preparing a new type of ceramic membranes from Syrian zeolite that was not previously used in this field. In this research, ceramic membranes were prepared from Syrian raw zeolite in several stages. Zeolite sample was characterized, grinded, mixed with boric acid, pressed to form desks, treated thermally according to experiment program, finally coated with silver nanoparticles. Specifications of prepared membranes were determined according to reference methods, effectiveness of prepar

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Publication Date
Wed Jul 09 2025
Journal Name
Resources
Enhancing Reservoir Modeling via the Black Oil Model for Horizontal Wells: South Rumaila Oilfield, Iraq
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Horizontal wells have revolutionized hydrocarbon production by enhancing recovery efficiency and reducing environmental impact. This paper presents an enhanced Black Oil Model simulator, written in Visual Basic, for three-dimensional two-phase (oil and water) flow through porous media. Unlike most existing tools, this simulator is customized for horizontal well modeling and calibrated using extensive historical data from the South Rumaila Oilfield, Iraq. The simulator first achieves a strong match with historical pressure data (1954–2004) using vertical wells, with an average deviation of less than 5% from observed pressures, and is then applied to forecast the performance of hypothetical horizontal wells (2008–2011). The result

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Publication Date
Wed Jan 01 2014
Journal Name
Siam Journal On Control And Optimization
A Duality Approach for Solving Control-Constrained Linear-Quadratic Optimal Control Problems
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Publication Date
Mon Jan 01 2024
Journal Name
Fifth International Conference On Applied Sciences: Icas2023
A modified Mobilenetv2 architecture for fire detection systems in open areas by deep learning
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This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.

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Publication Date
Tue Jan 14 2025
Journal Name
South Eastern European Journal Of Public Health
Deep learning-based threat Intelligence system for IoT Network in Compliance With IEEE Standard
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The continuous advancement in the use of the IoT has greatly transformed industries, though at the same time it has made the IoT network vulnerable to highly advanced cybercrimes. There are several limitations with traditional security measures for IoT; the protection of distributed and adaptive IoT systems requires new approaches. This research presents novel threat intelligence for IoT networks based on deep learning, which maintains compliance with IEEE standards. Interweaving artificial intelligence with standardization frameworks is the goal of the study and, thus, improves the identification, protection, and reduction of cyber threats impacting IoT environments. The study is systematic and begins by examining IoT-specific thre

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