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Drilling Optimization by Using Advanced Drilling Techniques in Buzurgan Oil Field
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Efficient and cost-effective drilling of directional wells necessitates the implementation of best drilling practices and advanced techniques to optimize drilling operations. Failure to adequately consider drilling risks can result in inefficient drilling operations and non-productive time (NPT). Although advanced drilling techniques may be expensive, they offer promising technical solutions for mitigating drilling risks. This paper aims to demonstrate the effectiveness of advanced drilling techniques in mitigating risks and improving drilling operations when compared to conventional drilling techniques. Specifically, the advanced drilling techniques employed in Buzurgan Oil Field, including vertical drilling with mud motor, managed pressure drilling (MPD), rotary steerable system (RSS), and expandable liner hanger (ELH), are investigated and evaluated through case study analyses, comparing their performance to that of conventional drilling techniques. The findings indicate that vertical drilling with mud motor exhibits superior drilling performance and wellbore verticality compared to conventional rotary drilling bottom hole assemblies (BHA) for drilling the 17 ½" hole section. MPD systems employed in the 12 ¼" hole section demonstrate safe drilling operations and higher rates of penetration (ROP) than conventional drilling methods. Rotary steerable systems exhibit reduced tortuosity and achieve higher ROP when compared to mud motor usage in the 8.5" and 6" hole sections. Lastly, investigations of expandable liner hanger cases reveal subpar cement quality in the first case and liner remedial work in the second case, highlighting the successful implementation of ELH techniques in the offset field. Overall, this paper highlights the advantages of utilizing advanced drilling techniques in Buzurgan Oil Field, showcasing their ability to mitigate drilling risks and enhance drilling operations when compared to conventional drilling approaches.

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Publication Date
Thu Jan 31 2019
Journal Name
Journal Of Engineering
Design of New Hybrid Neural Structure for Modeling and Controlling Nonlinear Systems
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This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number

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Publication Date
Wed Jun 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
Competitiveness of an enterprise under a flexible manufacturing system. Manufacturing strategy and flexibility - Case study
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The research has designed for studying the relationship between manufacturing strategy and its flexibility under the flexible manufacturing system with their reflection on the competitive environmental performance of the firm. To interpret and tackle the problem, a hypothesis has formulated stating that “ the competitive performance of a firm is interpreted by the manufacturing strategy and flexibility which are derived from the firm and its business  strategies under the flexible manufacturing system”. Related literatures with their theoretical dissertations, which enhanced the thoughtful content, have analyzed. An illustrative case study on the flexible manufacturing system at Toyota Motors Corporation working at the g

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Publication Date
Fri May 01 2015
Journal Name
Journal Of Engineering
A Real-Coded Genetic Algorithm with System Reduction and Restoration for Rapid and Reliable Power Flow Solution of Power Systems
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The paper presents a highly accurate power flow solution, reducing the possibility of ending at local minima, by using Real-Coded Genetic Algorithm (RCGA) with system reduction and restoration. The proposed method (RCGA) is modified to reduce the total computing time by reducing the system in size to that of the generator buses, which, for any realistic system, will be smaller in number, and the load buses are eliminated. Then solving the power flow problem for the generator buses only by real-coded GA to calculate the voltage phase angles, whereas the voltage magnitudes are specified resulted in reduced computation time for the solution. Then the system is restored by calculating the voltages of the load buses in terms

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Publication Date
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
Coronavirus Disease Diagnosis, Care and Prevention (COVID-19) Based on Decision Support System
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              Automated clinical decision support system (CDSS) acts as new paradigm in medical services today. CDSSs are utilized to increment specialists (doctors) in their perplexing decision-making. Along these lines, a reasonable decision support system is built up dependent on doctors' knowledge and data mining derivation framework so as to help with the interest the board in the medical care gracefully to control the Corona Virus Disease (COVID-19) virus pandemic and, generally, to determine the class of infection and to provide a suitable protocol treatment depending on the symptoms of patient. Firstly, it needs to determine the three early symptoms of COVID-19 pandemic criteria (fever, tiredness, dry cough and breat

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Publication Date
Sun Oct 01 2023
Journal Name
Baghdad Science Journal
The Necessary and Sufficient Optimality Conditions for a System of FOCPs with Caputo–Katugampola Derivatives
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The necessary optimality conditions with Lagrange multipliers  are studied and derived for a new class that includes the system of CaputoKatugampola fractional derivatives to the optimal control problems with considering the end time free. The formula for the integral by parts has been proven for the left CaputoKatugampola fractional derivative that contributes to the finding and deriving the necessary optimality conditions. Also, three special cases are obtained, including the study of the necessary optimality conditions when both the final time  and the final state  are fixed. According to convexity assumptions prove that necessary optimality conditions are sufficient optimality conditions.

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Publication Date
Tue Dec 29 2020
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The Impact of Electronic Payment systems on the Profitability of Banks: An applied research on a sample of Iraqi commercial banks
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Due to technological developments in the Iraqi banking sector, which is the use of electronic payment systems within the banking infrastructure. This has led to speed and accuracy in the completion of transactions, reduced costs, increased revenues and efficiency. This research examines the challenges and risks facing the Iraqi banking sector as a result of its use of electronic payment systems. And show its impact on the profitability of commercial banks. The research was based on the main hypothesis that there is a statistically significant moral impact relationship between electronic payment systems and the profitability of banks. Iraqi commercial banks were chosen as a research community, All Iraqi commercial banks that parti

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Publication Date
Wed May 17 2023
Journal Name
Journal Of Engineering
Development of Quality Rating Evaluation of Outgoing Product Case Study Applied at the General Company for Vegetable Oils
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Research covers the uses the method of Quality Rating Evaluation to evaluate the
quality of production through which a determination of product quality of its production in
order to determine the amount of sales hence the profits for the company. The most important
function is to satisfy consumer at reasonable prices. Methods were applied to the product
(toothpaste) in the General Company for Vegetable Oil – Almaamoon Factory .
The company's has obtained ISO-certified (ISO 9001-2008). Random samples of
final product intended for sale were collected from the store during months (February, April ,
June , October and December) for the year 2011 to determine the "quality rating " through
the applicat

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Publication Date
Thu Dec 01 2022
Journal Name
Iaes International Journal Of Artificial Intelligence
Reduced hardware requirements of deep neural network for breast cancer diagnosis
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Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration

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Publication Date
Mon Dec 02 2024
Journal Name
Al-iraqia Journal Of Scientific Engineering Research
Visible Light Communication System Integrating Road Signs with the Vehicle Network Grid
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Publication Date
Mon Dec 10 2018
Journal Name
Aro-the Scientific Journal Of Koya University
Membrane Computing for Real Medical Image Segmentation
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In this paper, membrane-based computing image segmentation, both region-based and edge-based, is proposed for medical images that involve two types of neighborhood relations between pixels. These neighborhood relations—namely, 4-adjacency and 8-adjacency of a membrane computing approach—construct a family of tissue-like P systems for segmenting actual 2D medical images in a constant number of steps; the two types of adjacency were compared using different hardware platforms. The process involves the generation of membrane-based segmentation rules for 2D medical images. The rules are written in the P-Lingua format and appended to the input image for visualization. The findings show that the neighborhood relations between pixels o

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