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Smart Well Modelling for As Reservoir in AG Oil Field
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Intelligent or smart completion wells vary from conventional wells. They have downhole flow control devices like Inflow Control Devices (ICD) and Interval Control Valves (ICV) to enhance reservoir management and control, optimizing hydrocarbon output and recovery. However, to explain their adoption and increase their economic return, a high level of justification is necessary. Smart horizontal wells also necessitate optimizing the number of valves, nozzles, and compartment length. A three-dimensional geological model of the As reservoir in AG oil field was used to see the influence of these factors on cumulative oil production and NPV. After creating the dynamic model for the As reservoir using the program Petrel (2017.4), we improve the robustness of forecasting production from smart wells using reservoir simulation. High-level details in the rock and fluid flow properties are required in the horizontal well region to capture the flow dynamics accurately. Thus, the study offers an enhanced method for predicting the performance of intelligent or smart wells in reservoir modeling. This model was history matched for a period of 20 years for three horizontal wells by using program Petrel (2017.4) and ECLIPS (2011). After successful validation of model on a field scale and well level, performance prediction was carried out to see the effect of (number of valves, number of nozzle and compartment length) using PICD/AFCV completion. Optimizing well performance entails lowering water-cut. From an economic viewpoint, the goal is to maximize NPV or profit, depending on the situation, from PICD wells, which compared to other wells.

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Publication Date
Sun May 01 2022
Journal Name
Expert Systems With Applications
Novel large scale brain network models for EEG epileptic pattern generations
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Background: Unlike normal EEG patterns, the epileptiform abnormal pattern is characterized by different mor phologies such as the high-frequency oscillations (HFOs) of ripples on spikes, spikes and waves, continuous and sporadic spikes, and ploy2 spikes. Several studies have reported that HFOs can be novel biomarkers in human epilepsy study. S) Method: To regenerate and investigate these patterns, we have proposed three large scale brain network models (BNM by linking the neural mass model (NMM) of Stefanescu-Jirsa 2D (S-J 2D) with our own structural con nectivity derived from the realistic biological data, so called, large-scale connectivity connectome. These models include multiple network connectivity of brain regions at different

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Publication Date
Mon Dec 04 2023
Journal Name
Aip Conf. Proc
Double LA-transform and their properties for solving partial differential equations
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Publication Date
Fri Jan 29 2021
Journal Name
International Journal Of Applied Mechanics And Engineering
Unified Methodology for Strength and Stress Analysis of Structural Concrete Members
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Abstract<p>In this paper, a methodology is presented for determining the stress and strain in structural concrete sections, also, for estimating the ultimate combination of axial forces and bending moments that produce failure. The structural concrete member may have a cross-section with an arbitrary configuration, the concrete region may consist of a set of subregions having different characteristics (i.e., different grades of concretes, or initially identical, but working with different stress-strain diagrams due to the effect of indirect reinforcement or the effect of confinement, etc.). This methodology is considering the tensile strain softening and tension stiffening of concrete in additio</p> ... Show More
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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
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
Sat May 30 2020
Journal Name
Neuroquantology
Comparative Study for Optoelectronic Properties of Zn (Te, Se) Solar Cells
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Publication Date
Fri Apr 28 2023
Journal Name
Surgical Neurology International
Neurosurgery theater-based learning: Etiquette and preparation tips for medical students
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Publication Date
Sat Oct 01 2022
Journal Name
The Egyptian Journal Of Hospital Medicine
Laminin Is a Promising Predictive Biomarker for Acute and Chronic Toxoplasmosis
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Publication Date
Wed Dec 25 2019
Journal Name
Journal Of Engineering
Design of Expert System for Managing the System of AthTharthar Lake
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The operation and management of water resources projects have direct and significant effects on the optimum use of water. Artificial intelligence techniques are a new tool used to help in making optimized decisions, based on knowledge bases in the planning, implementation, operation and management of projects as well as controlling flowing water quantities to prevent flooding and storage of excess water and use it during drought.

 In this research, an Expert System was designed for operating and managing the system of AthTharthar Lake (ESSTAR). It was applied for all expected conditions of flow, including the cases of   drought, normal flow, and during floods. Moreover, the cases of hypothetical op

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Publication Date
Sat Mar 30 2013
Journal Name
College Of Islamic Sciences
The comparative approach (stabilizer) and the need for Arabic to it
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Linguistic research according to modern curricula:
   It is one of the important matters that occupy the ideas of those concerned with linguistic studies, whether Arabic or otherwise. Recent years have witnessed the advancement of this methodological approach, and books and studies in Arabic have been written on important, multifaceted issues, of grammatical and linguistic origins, and their balance with new developments and ideas attracted mostly from Western studies.
    The comparative approach - as they call it - is one of the modern approaches that is based on balancing a language with other sisters belonging to its family, to reach similarities and differences between them, and to know the c

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