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Geomechanical Modeling and Artificial Neural Network Technique for Predicting Breakout Failure in Nasiriyah Oilfield
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Wellbore instability is one of the major issues observed throughout the drilling operation. Various wellbore instability issues may occur during drilling operations, including tight holes, borehole collapse, stuck pipe, and shale caving. Rock failure criteria are important in geomechanical analysis since they predict shear and tensile failures. A suitable failure criterion must match the rock failure, which a caliper log can detect to estimate the optimal mud weight. Lack of data makes certain wells' caliper logs unavailable. This makes it difficult to validate the performance of each failure criterion. This paper proposes an approach for predicting the breakout zones in the Nasiriyah oil field using an artificial neural network. It also presents the optimal mud weight window for this field, which can be used to optimise the mud weights to minimise the wellbore instability issues. The results showed that an artificial neural network is a powerful tool for determining the breakout zones using the input data. The obtaining root mean square error and the determination coefficient were respectively 0.0082 and 0.959, by which the 1D MEM gave a high match between the predicted wellbore instabilities using the Mogi-failure criterion and the predicted breakout using the ANN model. Most borehole enlargements occur due to formation shear failures because of using low mud weights during drilling. The conclusion clarify the1.35 g/cc is the optimal mud weights for drilling new wells in this field of interest with fewer drilling issues.

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Publication Date
Sun Jan 01 2023
Journal Name
Communications In Mathematical Biology And Neuroscience
A reliable numerical simulation technique for solving COVID-19 model
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Publication Date
Mon Feb 18 2019
Journal Name
Iraqi Journal Of Physics
Different methods for characterizing surface roughness using laser speckle technique
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In this work, results from an optical technique (laser speckle technique) for measuring surface roughness was done by using statistical properties of speckle pattern from the point of view of computer image texture analysis. Four calibration relationships were used to cover wide range of measurement with the same laser speckle technique. The first one is based on intensity contrast of the speckle, the second is based on analysis of speckle binary image,  the third is on size of speckle pattern spot, and the latest one is based on characterization of the energy feature of the gray level co-occurrence matrices for the speckle pattern. By these calibration relationships surface roughness of an object surface can be evaluated within the

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Publication Date
Thu Mar 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
Nadaraya-Watson Estimator a Smoothing Technique for Estimating Regression Function
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    The using of the parametric models and the subsequent estimation methods require the presence of many of the primary conditions to be met by those models to represent the population under study adequately, these prompting researchers to search for more flexible models of parametric models and these models were nonparametric models.

    In this manuscript were compared to the so-called Nadaraya-Watson estimator in two cases (use of fixed bandwidth and variable) through simulation with different models and samples sizes.  Through simulation experiments and the results showed that for the first and second models preferred NW with fixed bandwidth fo

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Publication Date
Wed Jan 01 2025
Journal Name
Journal Of Interdisciplinary Mathematics
Analytical solutions for nonlinear differential equations via differential transform technique
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A relatively novel technique differential equations named Differential Transform Technique (DTM) is proposed. The evaluation of this approach is based on an iterative method in series form. Here, First give several basic definitions and properties of DTM, and applied various examples for the proposed method are tested to show the efficiency and accuracy to get the solutions of non-linear pantograph equation with elegantly computed components. In addition to solving the problems efficiently and rapidly, The advantage of the suggested approach is that it produces an analytical approach with fewer terms in a convergent series form.

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Publication Date
Thu Oct 18 2018
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
STUDY OF THE TEMPORAL EFFECT OF THE LEVEL OF THE CREATINE KINASE ENZYME CK-MB AND SOME BIOMARKERS IN PATIENTS WITH MYOCARDIAL INFARCTION AND HEART FAILURE IN RAMADI CITY: STUDY OF THE TEMPORAL EFFECT OF THE LEVEL OF THE CREATINE KINASE ENZYME CK-MB AND SOME BIOMARKERS IN PATIENTS WITH MYOCARDIAL INFARCTION AND HEART FAILURE IN RAMADI CITY
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The current study is designed to achieve the goal of early detection of heart disease because it is the main risk of death. Some biomarkers were measured as well as the percentage of the effect of certain risk factors in people with myocardial infarction and heart failure. The study included 40 serum samples from people with heart disease. The effectiveness of the creatine kinase (CK-MB), as well as its temporal and albumin effects, as well as sodium ions in people with myocardial infarction and heart failure, were compared with the control group. as shown below:

-The first group consisted of 25 blood samples from people with myocardial infarction and 15 serum samples from people with heart failure. Blood

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
The Effect Of Optimizers On The Generalizability Additive Neural Attention For Customer Support Twitter Dataset In Chatbot Application
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When optimizing the performance of neural network-based chatbots, determining the optimizer is one of the most important aspects. Optimizers primarily control the adjustment of model parameters such as weight and bias to minimize a loss function during training. Adaptive optimizers such as ADAM have become a standard choice and are widely used for their invariant parameter updates' magnitudes concerning gradient scale variations, but often pose generalization problems. Alternatively, Stochastic Gradient Descent (SGD) with Momentum and the extension of ADAM, the ADAMW, offers several advantages. This study aims to compare and examine the effects of these optimizers on the chatbot CST dataset. The effectiveness of each optimizer is evaluat

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Publication Date
Tue Jun 01 2021
Journal Name
International Journal Of Nonlinear Analysis And Applications
A proposed method for cleaning data from outlier values using the robust rfch method in structural equation modeling
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Publication Date
Fri Jul 26 2019
Journal Name
Dental Materials Journal
Semi-interpenetrating network composites reinforced with Kevlar fibers for dental post fabrication
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Publication Date
Mon Sep 30 2002
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Modeling of a Sulfonation Reactor in a Detergent Factory
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Publication Date
Sun Nov 10 2019
Journal Name
Journal Of Engineering And Applied Sciences
Discrete Fracture Network and Fractured Reservoir Characterization in Khabaz Field-Tertiary Formation
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