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Wellbore Trajectory Optimization Using Rate of Penetration and Wellbore Stability Analysis
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Drilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability.

In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation pore pressure, and in-situ stresses of the studied area were included as inputs. The second step was by optimizing the process using a genetic algorithm (GA), as a class of optimizing methods for complex functions, to obtain the maximum ROP along with the related wellbore trajectory (AZI and INC). Finally, the suggested azimuth (AZI) and inclination (INC) are premeditated by considering the results of wellbore stability analysis using wireline logging measurements, core and drilling data from the offset wells.

The results showed that the optimized wellbore trajectory based on wellbore stability analysis was compatible with the results of the genetic algorithm (GA) that used to reach higher ROP. The recommended orientation that leads to maximum ROP and maintains the stability of drilling deviated wells (i.e., inclination ranged between 40°—50°) is parallel to (140°—150°) direction. The present study emphasizes that the proposed methodology can be applied as a cost-effective tool to optimize the wellbore trajectory and to calculate approximately the drilling time for future highly deviated wells.

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agriculture And Statistical Science
COMPARISON OF FORECASTING OF THE RISK OF CORONAVIRUS (COVID-19) IN HIGH-QUALITY AND LOW-QUALITY HEALTHCARE SYSTEMS, USING ANN MODELS
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COVID-19 is a disease that has abnormal over 170 nations worldwide. The number of infected people (either sick or dead) has been growing at a worrying ratio in virtually all the affected countries. Forecasting procedures can be instructed so helping in scheming well plans and in captivating creative conclusions. These procedures measure the conditions of the previous thus allowing well forecasts around the state to arise in the future. These predictions strength helps to make contradiction of likely pressures and significances. Forecasting procedures production a very main character in elastic precise predictions. In this case study used two models in order to diagnose optimal approach by compared the outputs. This study was introduce

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Publication Date
Fri Mar 29 2024
Journal Name
مجلة العلوم التربوية والنفسية
Needs in the stories of the Brothers Grimm (a study in content analysis)
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The current study aims to identify the needs in the stories of the Brothers Grimm. The research sample consisted of (3) stories, namely: 1- The story of the Thorn Rose (Sleeping Beauty) 2- The story of Snow White 3- The story of Little Red Riding Hood. The number of pages analyzed reached (15.5) pages, and to achieve the research objectives, Murray's classification of needs was adopted, which contains (36) basic needs that are further divided into (129) sub-needs. The idea was adopted as a unit of analysis and repetition as a unit of enumeration, Reliability was extracted in two ways: 1- Agreement between the researcher and himself over time, where the agreement coefficient reached 97%. The second was agreement between the researcher and tw

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Publication Date
Tue Dec 01 2009
Journal Name
Journal Of Economics And Administrative Sciences
Analysis of relations and forces of production in extraction And pearl industry in the Arabian Gulf 1900-1950 *
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بسبب محدودية الموارد الطبيعية، فأن سكان الخليج ومنذ القدم وجهوا جلّ نشاطاتهم توجهاً بحرياً: صيد الاسماك وصناعة اللؤلؤ العنصر الرئيس في حجم التشغيل، وتكوين الفائض الاقتصادي في المنطقة آنذاك.

لقد تزايدت أهمية هذا النشاط بخاصة بعد النصف الثاني من القرن التاسع عشر، لرواج تجارة اللؤلؤ عالمياً، وأنفتاح الخليج على الدول الاوروبية التي شهدت نهضة صناعية متسارعة، وحيث وصلت الخليج العديد من بضائع

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Publication Date
Sun Sep 07 2014
Journal Name
Baghdad Science Journal
Analysis of Fatty Acid Composition in the Seed and flower oil of Syrian Ligustrun Lucidum and olive oil
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The fatty acid composition in the seed and flower of Ligustrun lucidum and olive oil was studied by Gas Chromatography. Results showed that the main components of seed oil were Palmitic (C16:0) 5,893% ,Palmitolic acid (C16:1)0,398%, Steaeic (C18:0)2,911% ,Oleic (C18:1)74,984%,Linoleic (C18:2) 12,959%,and Linolenic (C18:3) 0,997%. The proportion of unsaturated fatty acid was above 89,338%, so the seed oil of L. lucidum ait belonged to unsaturated oil which possessed promising application. The components of flower oil were Palmitic (C16:0) 65,674% ,Palmitolic acid (C16:1)6,516%, Steaeic (C18:0)2,641% ,Oleic (C18:1)14,707%,Linoleic (C18:2) 3,113%,and Linolenic (C18:3) 2,70%. The proportion of unsaturated fatty acid and saturated fatty acid wa

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Publication Date
Sun Feb 12 2012
Journal Name
Institute Of Advanced Studies In English
Cohesive Devices in English and Arabic with Analysis of Two of Hemingway's Novels and their Translations
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DBN Rashid, 2012 - Cited by 2

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Publication Date
Sat Aug 01 2020
Journal Name
Journal Of Engineering
Statistical Analysis of Metal Removal during Magnetic Abrasive Finishing Process
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This work aims to provide a statistical analysis of metal removal during the Magnetic Abrasive Finishing process (MAF) and find out the mathematical model which describes the relationship between the process parameters and metal removal, also estimate the impact of the parameters on metal removal. In this study, the single point incremental forming was used to form the truncated cone made of low carbon steel (1008-AISI) based on the Z-level tool path. Then the finishing was accomplished using a magnetic abrasive process based on the Box-Behnken design of the experiment using Minitab 17 software was used to finish the surface of the formed truncated cone. The influences of different parameters (feed rate, machining step s

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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network
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Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

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Publication Date
Thu Aug 31 2017
Journal Name
Journal Of Engineering
Optimum Dimensions of Hydraulic Structures and Foundation Using Genetic Algorithm coupled with Artificial Neural Network
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      A model using the artificial neural networks and genetic algorithm technique is developed for obtaining optimum dimensions of the foundation length and protections of small hydraulic structures. The procedure involves optimizing an objective function comprising a weighted summation of the state variables. The decision variables considered in the optimization are the upstream and downstream cutoffs lengths and their angles of inclination, the foundation length, and the length of the downstream soil protection. These were obtained for a given maximum difference in head, depth of impervious layer and degree of anisotropy. The optimization carried out is subjected to constraints that ensure a safe structure aga

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Publication Date
Tue Sep 01 2020
Journal Name
Baghdad Science Journal
Developing Arabic License Plate Recognition System Using Artificial Neural Network and Canny Edge Detection
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            In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the

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Publication Date
Fri Jul 01 2022
Journal Name
International Journal Of Nonlinear Analysis And Applications
Survey on distributed denial of service attack detection using deep learning: A review
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Distributed Denial of Service (DDoS) attacks on Web-based services have grown in both number and sophistication with the rise of advanced wireless technology and modern computing paradigms. Detecting these attacks in the sea of communication packets is very important. There were a lot of DDoS attacks that were directed at the network and transport layers at first. During the past few years, attackers have changed their strategies to try to get into the application layer. The application layer attacks could be more harmful and stealthier because the attack traffic and the normal traffic flows cannot be told apart. Distributed attacks are hard to fight because they can affect real computing resources as well as network bandwidth. DDoS attacks

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