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Modeling Rate of Penetration using Artificial Intelligent System and Multiple Regression Analysis
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Abstract<p>Over the years, the prediction of penetration rate (ROP) has played a key rule for drilling engineers due it is effect on the optimization of various parameters that related to substantial cost saving. Many researchers have continually worked to optimize penetration rate. A major issue with most published studies is that there is no simple model currently available to guarantee the ROP prediction.</p><p>The main objective of this study is to further improve ROP prediction using two predictive methods, multiple regression analysis (MRA) and artificial neural networks (ANNs). A field case in SE Iraq was conducted to predict the ROP from a large number of parameters. A databases from one well drilled in carbonate environments were subjected to the predictive methods. Each raw dataset is described by eight parameters including rate of penetration (ROP), true vertical depth (TVD), weight on bit (WOB), bit rotational speed (RPM), torque (TQ), flow rate (Q), equivalent circulating density (ECD), standpipe pressure (SPP), and unconfined compressive strength (UCS). First, both MRA and ANNs are tested as predictive methods. The prediction capacity of each model was also verified by using two-based error metrics: the determination coefficient (R2) and the mean square error (MSE).</p><p>The current results support the evidence that MRA and ANNs are able to be effectively utilize the drilling data, and thus provide accurate ROP prediction. However, more attention to the multiple regression analysis is required where it is implemented for ROP prediction. ANNs appear to be more conservative in predicting ROP than MRA as indicated by a higher value R2 (0.96) and lower value MSE (1.89) of the ANN model. Considering the input parameters, the obtained results showed that TVD, WOB, RPM, SPP, and ECD had the greatest effect on estimated ROP-conditions, followed in decreasing by pump flow rate, drilling torque, and rock strength. Another important point that highlights in this study is that the drilling rate may increase with depth in carbonate rocks because of their heterogeneity. This study presents new models to estimate ROP from other parameters which can help the driller to achieve an optimal drilling rate through monitoring controllable parameters.</p>
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Publication Date
Sun Dec 04 2016
Journal Name
Baghdad Science Journal
Transition Metal Complexes with Tridentate Ligand: Preparation, Spectroscopic Characterization, Thermal Analysis and Structural Studies
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New series of metal ions complexes have been prepared from the new ligand 1,5- Dimethyl-4- (5-oxohexan-2- ylideneamino) -2-phenyl- 1H-pyrazol-3 (2H)-one derived from 2,5-hexandione and 4-aminophenazone. Then, its V(IV), Ni(II), Cu(II), Pd(II), Re(V) and Pt(IV) complexes prepared. The compounds have been characterized by FT-IR, UV-Vis, mass and 1H and 13C-NMR spectra, TGA curve, magnetic moment, elemental microanalyses (C.H.N.O.), chloride containing, Atomic absorption and molar conductance. Hyper Chem-8 program has been used to predict structural geometries of compounds in gas phase, the heat of formation, (binding, total and electronic energy) and dipole moment at 298 K.

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Publication Date
Fri Feb 28 2020
Journal Name
Iraqi Journal Of Science
Homotopy Perturbation Method and Convergence Analysis for the Linear Mixed Volterra-Fredholm Integral Equations
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In this paper, the homotopy perturbation method is presented for solving the second kind linear mixed Volterra-Fredholm integral equations. Then, Aitken method is used to accelerate the convergence. In this method, a series will be constructed whose sum is the solution of the considered integral equation. Convergence of the constructed series is discussed, and its proof is given; the error estimation is also obtained. For more illustration, the method is applied on several examples and programs, which are written in MATLAB (R2015a) to compute the results. The absolute errors are computed to clarify the efficiency of the method.

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Publication Date
Sun Dec 05 2021
Journal Name
Iraqi Journal Of Science
Climatic Analysis and Climatic Water Balance Determination for Al- Yusufiyah Area, Southern Baghdad, Iraq
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The Climatic parameters for the years (1985-2015) were collected from Baghdad
meteorological station and then were applied to evaluate the climatic conditions for
the Al-Yusufyiah area south Baghdad. The total annual rainfall is (119.65 mm),
while the total annual evaporation is (3201.7 mm), relative humidity is (43.62%),
sunshine (8.76 h/day), temperature (23.28 C◦) and wind speed (3.06 m/sec). Climate
of the study area is described as an arid according to classification of (Kettaneh and
Gangopadhyaya, 1974), (Mather, 1973), and (Al-Kubaisi, 2004). Mean monthly
water surplus for the period (1985-2015) was recorded in the study area about (4.7
mm) in November, (11.67 mm) in December, (20.56 mm) in January and (6

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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Engineering
Prediction of Monthly Fluoride Content in Tigris River using SARIMA Model in R Software
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The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2,0,0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlation coefficien

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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Engineering
Prediction of Monthly Fluoride Content in Tigris River using SARIMA Model in R Software
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The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2, 0, 0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlat

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Publication Date
Fri Oct 25 2024
Journal Name
The Review Of Contemporary Scientific And Academic Studies
The Representation of Men and Women in the Black and White Streams of the Second Wave of Feminism: A Corpus Stylistic Analysis
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Publication Date
Fri Jun 17 2022
Journal Name
Journal Of Baghdad College Of Dentistry
Clinicopathological analysis of 80 cases of oral lobular and non lobular capillary hemangioma (pyogenic granuloma): A Retrospective study
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Background: Oral pyogenic granuloma (PG) is a clinicopathological entity that could develop due to the reaction to a variety of stimuli, such as low-grade local irritation, traumatic damage, and hormonal stimulation. There are two histopathological types of pyogenic granuloma; lobular type -capillary hemangioma (LCH) and non-lobular type; with PG,LCH has highly vascular, diffuse capillary growth while non- lobular variant mimicking granulation tissue with heavily inflammated stroma. The study aims were to review the clinical  and histopathological spectrum of an oral pyogenic granuloma from different intraoral sites in order to avoid diagnostic pitfalls associated with similar morphological lesions and to determine

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Publication Date
Sun Jul 01 2018
Journal Name
Comprehensive Psychiatry
Complexity analysis of spontaneous brain activity in mood disorders: A magnetoencephalography study of bipolar disorder and major depression
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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Strain Analysis of Surface Cracked Thin Flat Plate under Cycling Impact Loading Effect
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In this work, strains and dynamic crack growth were studied and analyzed in thin flat plate with a surface crack at the center, subjected to cycling low velocity impact loading for two types of aluminum plates (2024, 6061). Experimental and numerical methods were implemented to achieve this research. Numerical analysis using program (ANSYS11-APDL) based on finite element method used to analysis the strains with respect to time at crack tip and then find the velocity of the crack growth under cycling impact loading. In the experimental work, a rig was designed and manufactured to applying the cycling impact loading on the cracked specimens. The grid points was screened in front of the crack tip to measure the elastic-plas

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Publication Date
Mon Nov 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
The Use of Auto-Regressive Distributed Lag Method in Investigating The Impact of Interest Rate on Foreign Direct Investment in Yemen for the Period 1990-2018
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 Foreign direct investment has seen increasing interest worldwide, especially in developing economies. However, statistics have shown that Yemen received fluctuating FDI inflows during the period under study. Against this background, this research seeks to determine the relationship and impact of interest rates on FDI flows. The study also found other determinants that greatly affected FDI inflows in Yemen for the period 1990-2018. Study data collected from the World Bank and International Monetary Fund databases. It also ensured that the time series were made balanced and interconnected, and then the Auto Regressive Distributed Lag method used in the analysis. The results showed that the interest rates and

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