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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
Thu Dec 28 2017
Journal Name
Al-khwarizmi Engineering Journal
An Autocorrelative Approach for EMG Time-Frequency Analysis
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As they are the smallest functional parts of the muscle, motor units (MUs) are considered as the basic building blocks of the neuromuscular system. Monitoring MU recruitment, de-recruitment, and firing rate (by either invasive or surface techniques) leads to the understanding of motor control strategies and of their pathological alterations. EMG signal decomposition is the process of identification and classification of individual motor unit action potentials (MUAPs) in the interference pattern detected with either intramuscular or surface electrodes. Signal processing techniques were used in EMG signal decomposition to understand fundamental and physiological issues. Many techniques have been developed to decompose intramuscularly detec

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Publication Date
Thu Apr 01 2021
Journal Name
Chaos, Solitons & Fractals
Modeling and analysis of an SI1I2R epidemic model with nonlinear incidence and general recovery functions of I1
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In this paper, we established a mathematical model of an SI1I2R epidemic disease with saturated incidence and general recovery functions of the first disease I1. Considering the basic reproduction number, we obtained conditions for both disease-free and co-existing cases. The equilibrium points local stability is verified by using the Routh-Hurwitz criterion, while for the global stability, we used a suitable Lyapunov function to analyze the endemic spread of the positive equilibrium point. Moreover, we carried out the local bifurcation around both equilibrium points (disease-free and co-existing), where we obtained that the disease-free equilibrium point undergoes a transcritical bifurcation. We conduct numerical simulations that suppo

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Publication Date
Sun Jan 01 2023
Journal Name
International Journal Of Physiology, Nutrition And Physical Education
The effect of effort perception training according to race speed rhythm control for developing speed endurance, adapting maximum heart rate, and achieving 3000 m running/hurdles for men
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Publication Date
Mon Jan 02 2017
Journal Name
Intraventricular Pressure Ventr
The Use of Rate of Increase of Intraventricular Pressure During Isovolumetric Contraction (dP/dt) in Assessment of Left Ventricular Function in Acute Coronary Syndrome
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BACKGROUND: Acute coronary syndrome (ACS) is the clinical manifestation of acutely diminished coronary arterial blood supply. The rate of increase of intraventricular pressure during isovolumetric contraction (left ventricular dP/dt) represents the rate of change of pressure during ejection. OBJECTIVE: The aim of this study is to evaluate the usefulness of the rate of increase of intraventricular pressure during isovolumetric contraction (dP/dt) in assessment of left ventricular function in patients with acute coronary syndrome and its relation to certain clinical and echocardiographic features. PATIENTS AND METHODS: The study is a cross sectional study including 50 patients with an established diagnosis of acute coronary syndrome. The

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Publication Date
Sun Aug 23 2020
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The impact of the capital increase in the rate of return on stock price: Applied in the study of a sample of Iraqi banks
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The capital banking foundation stone upon which the bank in the practice of business activities, the more capital a good financial adequacy of the increased bank's ability to grant credit and expand the various activities and provide a safety element for depositors and other sources of funding to achieve profits and increase the trading volume of the shares, causing the rise the rate of return for the shares of banks and have the Central Bank as head of the banking system by issuing instructions capital increase banking, according to the requirements of economic development and increase gross domestic product by supporting investment projects that are financed through banks, the research aims to show the extent of the banks commitment to

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Publication Date
Wed Feb 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering
Classification of COVID-19 from CT chest images using Convolutional Wavelet Neural Network
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<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

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Publication Date
Fri Jul 01 2016
Journal Name
Journal Of Engineering
Buckling Analysis of Edge Cracked Sandwich Plate
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This work presents mainly the buckling load of sandwich plates with or without crack for different cases. The buckling loads are analyzed experimentally and numerically by using ANSYS 15. The experimental investigation was to fabricate the cracked sandwich plate from stainless steel and PVC to find mechanical properties of stainless steel and PVC such as young modulus. The buckling load for different aspect ratio, crack length, cracked location and plate without crack found. The experimental results were compared with that found from ANSYS program. Present of crack is decreased the buckling load and that depends on crack size, crack location and aspect ratio.

 

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Publication Date
Tue Jan 12 2016
Journal Name
Spectral Physics Communications
Photobleaching Analysis of Binary Lasing Compound Systems
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Publication Date
Tue Jul 01 2014
Journal Name
Political Sciences Journal
Business partnerships analysis of Iraq's 2003 -2013
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تحليل الشراكات التجارية للعراق 2003-2013

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Publication Date
Sun Sep 01 2019
Journal Name
Al Adab
Cognitive Stylistic Analysis of Daily Yahoo Storie
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Cognitive stylistics is one discipline of applied linguistics that relies on the reader’s interpretation and inference of the meaning of the text depending on his background knowledge. It studies how the reader understands the text and mapping it with his real experiences (Jeffries and McIntyre,2010). The present study is a cognitive stylistic analysis of digital stories. Digital stories are short narratives made by a combination of different sorts of digital media such as pictures, audios and videos. These digital media are employed to tell stories about oneself, famous people, and important events. The analyzed stories are selected from “Daily Yahoo Stories” and are analyzed according to Lakoff (1993) approach, The analysis investig

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