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A Survey of Infill Well Location Optimization Techniques
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The maximization of the net present value of the investment in oil field improvements is greatly aided by the optimization of well location, which plays a significant role in the production of oil. However, using of optimization methods in well placement developments is exceedingly difficult since the well placement optimization scenario involves a large number of choice variables, objective functions, and restrictions. In addition, a wide variety of computational approaches, both traditional and unconventional, have been applied in order to maximize the efficiency of well installation operations. This research demonstrates how optimization approaches used in well placement have progressed since the last time they were examined. Following that, the research looked at a variety of different optimization strategies, and it demonstrated the limitations of each strategy as well as the scope of its application in order to achieve a suitable level of accuracy and simulation run time. In conclusion, this study presents an all-encompassing analysis of the well location optimization approaches that are applied in the petroleum engineering area, ranging from traditional methods to contemporary methods that make use of artificial intelligence.

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Publication Date
Thu Oct 18 2018
Journal Name
Al–bahith Al–a'alami
The Pressures Affecting the Performance of Iraqi Media before the Legislative Elections of 2018 (Iraqi Satellite News Channel- as a Model): A Survey Study  Dr.Safad Husam Hammody
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The modernity of election practices of the elections in Iraq, according to the democratic approach, has led to a struggle between political rival forces reflecting a deep pressure on the tools involved in the management, marketing or control of these elections across the general social level. Hence the problem of research resides in answering the following question: What is the nature and size of the pressures affecting the media performance of Al-Iraqia News channel before the legislative elections of 2018 in Iraq?
      The objectives of the research were the following:
1. to identify the nature of the pressures that limit the Al-Iraqia News channel’s perfo

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Publication Date
Tue Jul 19 2022
Journal Name
Handbook Of Moth-flame Optimization Algorithm
Moth-Flame Optimization Algorithm, Arithmetic Optimization Algorithm, Aquila Optimizer, Gray Wolf Optimizer, and Sine Cosine Algorithm
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Publication Date
Wed Dec 22 2021
Journal Name
Plos One
Awareness and preparedness of healthcare workers against the first wave of the COVID-19 pandemic: A cross-sectional survey across 57 countries
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Background

Since the COVID-19 pandemic began, there have been concerns related to the preparedness of healthcare workers (HCWs). This study aimed to describe the level of awareness and preparedness of hospital HCWs at the time of the first wave.

Methods

This multinational, multicenter, cross-sectional survey was conducted among hospital HCWs from February to May 2020. We used a hierarchical logistic regression multivariate analysis to adjust the influence of variables based on awareness and preparedness. We then used association rule mining to identify relationships between HCW confidence in handling suspected

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Publication Date
Wed Feb 15 2017
Journal Name
كلية بغداد للعلوم الاقتصادية الجامعة
Competitiveness of business organizations according to the role of knowledge management and customer orientation: a comparative survey study in Iraqi business organizations
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The research aims to reach a set of objectives concerning creation a clear vision about conceptual, philosophical and practical dimension of relations, and effects between knowledge management, costumer orientation and competitiveness to construct a framework of a pragmatic model as a solution to research problem and its questions which the main one is about the role of knowledge management and costumer orientation in competitiveness of business organizations. To achieving this goal, it was necessary to make, in priory, a review and discussion to the theoretical dimension of research variables to have a clear vision about constructing hypostatical research model implying a set of hypotheses which, by proving them in companies studied, repr

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Publication Date
Wed Feb 01 2023
Journal Name
Practice Periodical On Structural Design And Construction
Leading Indicators of the Health and Well-Being of the Construction Workforce: Perception of Industry Professionals
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Publication Date
Sat Jan 01 2022
Journal Name
International Journal Of Mechanical Engineering
Process Parameters Optimization in Single Point Incremental Forming Of Al1050
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This work aims to optimize surface roughness, wall angle deviation, and average wall thickness as output responses of ALuminium-1050 alloy cone formed by the single point incremental sheet metal forming process. The experiments are accomplished based on the use of a mixed level Taguchi experimental design with an L18 orthogonal array. Six levels of step depth, three levels of tool diameter, feed rate, and tool rotational speed have been considered as input process parameters. The analyses of variance (ANOVA) have been used to investigate the significance of parameters and the effect of their levels for minimum surface roughness, minimum wall angle deviation, and maximum average wall thickness. The results indicate that step depth and tool r

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Publication Date
Mon Dec 10 2018
Journal Name
Day 1 Mon, December 10, 2018
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

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Publication Date
Mon Dec 10 2018
Journal Name
Day 1 Mon, December 10, 2018
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

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Publication Date
Fri Jan 01 2021
Journal Name
Signals And Communication Technology
Survey on Twitter Sentiment Analysis: Architecture, Classifications, and Challenges
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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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