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Studying the Effect of Permeability Prediction on Reservoir History Matching by Using Artificial Intelligence and Flow Zone Indicator Methods
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The map of permeability distribution in the reservoirs is considered one of the most essential steps of the geologic model building due to its governing the fluid flow through the reservoir which makes it the most influential parameter on the history matching than other parameters. For that, it is the most petrophysical properties that are tuned during the history matching. Unfortunately, the prediction of the relationship between static petrophysics (porosity) and dynamic petrophysics (permeability) from conventional wells logs has a sophisticated problem to solve by conventional statistical methods for heterogeneous formations. For that, this paper examines the ability and performance of the artificial intelligence method in permeability prediction and compared its results with the flow zone indicator methods for a carbonate heterogeneous Iraqi formation. The methodology of the research can be Summarized by permeability was estimated by using two methods: Flow zone indicator and Artificial intelligence, two reservoir models are built, where the difference between them is in permeability method estimation, and the simulation run will be conducted on both of the models, and the permeability estimation methods will be examined by comparing their effect on the model history matching. The results showed that the model with permeability predicted by using artificial intelligence matched the observed data for different reservoir responses more accurately than the model with permeability predicted by the flow zone indicator method. That conclusion is represented by good matching between observed data and simulated results for all reservoir responses such for the artificial intelligence model than the flow zone indicator model.

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Publication Date
Mon Dec 30 2019
Journal Name
College Of Islamic Sciences
The effect of context on some Quranic methods
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Each book has a specific style in which its author walks on it from its beginning to its end, and the Holy Qur’an is a book that compiled many methods that were indicative of its miracle, and that it is one unit even though it has been astrologer for twenty-three years.
There is no doubt that knowledge of the Qur’anic methods is one of the pillars of the approach that deals with any of the Qur’an, and the multiplicity of Qur’anic methods is a fact that has many causes. It has been expressed by the Qur’anic discharge and the conjugation of verses to bring them to different methods, and on multiple forms such as nominal, actual, singular Qur’an, presentation, delay, deletion, mention, abbreviation and redundancy. The Qur'ani

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Publication Date
Sun Jan 01 2023
Journal Name
8th Engineering And 2nd International Conference For College Of Engineering – University Of Baghdad: Coec8-2021 Proceedings
Prediction of consolidation due to dewatering by using MATLAB software
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Publication Date
Sun Mar 13 2016
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
Isolation and Identification of food Probiotic Saccharomyces boulardii by using traditional methods, Vitek 2 system and molecular identification methods.: Isolation and Identification of food Probiotic Saccharomyces boulardii by using traditional methods, Vitek 2 system and molecular identification methods.
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This study was aimed to isolate and identify Saccharomyces boulardii from Mangosteen fruits (Garcinia mangostana L.) by traditional and molecular identification methods To get safe and healthy foods probiotics for use, The isolates and two commercial strains were subjected to cultural, morphological and biochemical tests, The colonies of the isolates were spherical, smooth, mucoidal, dull and white to cream colour on SD agar media .The shape of cells was globose to ovoid and sometimes with budding, in a single form or clustered like a beehive. The isolates and two commercial strains were unable to metabolized galactose and lactose , Results shows that all isolates were unable to utilize potassium nitrate and not grow in the presence of (

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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Proposition of New Ensemble Data-Intelligence Models for Surface Water Quality Prediction
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Publication Date
Fri Mar 01 2024
Journal Name
International Journal Of Medical Informatics
An artificial intelligence approach to predict infants’ health status at birth
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Publication Date
Mon Dec 02 2024
Journal Name
Engineering, Technology & Applied Science Research
An Artificial Neural Network Prediction Model of GFRP Residual Tensile Strength
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This study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur

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Publication Date
Sat Jul 22 2023
Journal Name
Journal Of Engineering
Prediction of Smear Effect on the Bearing Capacity of Driven Piles
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This paper deals with prediction the effect of soil remoulding (smear) on the ultimate bearing capacity of driven piles. The proposed method based on detecting the decrease in ultimate bearing capacity of the pile shaft (excluding the share of pile tip) after sliding downward. This was done via conducting an experimental study on three installed R.C piles in a sandy clayey silt soil. The piles were installed so that a gap space is left between its tip and the base of borehole. The piles were tested for ultimate bearing capacity
according to ASTM D1143 in three stages. Between each two stages the pile was jacked inside the borehole until a sliding of about 200mm is achieved to simulate the soil remoulding due to actual pile driving. T

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Publication Date
Sat Oct 06 2012
Journal Name
Journal Of Engineering
Prediction of Smear Effect on the Bearing Capacity of Driven Piles
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Publication Date
Mon Oct 01 2012
Journal Name
Journal Of Engineering
Prediction of Smear Effect on the Bearing Capacity of Driven Piles
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This paper deals with prediction the effect of soil re-moulding (smear) on the ultimate bearing capacity of driven piles. The proposed method based on detecting the decrease in ultimate bearing capacity of the pile shaft (excluding the share of pile tip) after sliding downward. This was done via conducting an experimental study on three installed R.C piles in a sandy clayey silt soil. The piles were installed so that a gap space is left between its tip and the base of borehole. The piles were tested for ultimate bearing capacity according to ASTM D1143 in three stages. Between each two stages the pile was jacked inside the borehole until a sliding of about 200mm is achieved to simulate the soil re-moulding due to actual pile driving. The re

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Publication Date
Mon Dec 31 2012
Journal Name
Al-khwarizmi Engineering Journal
The Effect of Doppler Phenomenon on the Speed of Blood Flow
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This research studying the phenomenon of Doppler (frequency Doppler) as a method through which the direction and speed of the blood cells flows in blood vessels wear measured. This Doppler frequency is relied upon in medicine for measuring the speed of blood flow, because the blood flow is an important concept from the concepts of medicine. It represents the function and efficient of the heart and blood vessels in the body so any defect in this function will appear as a change in the speed of blood flow from the normal value assumed. As this speed changes alot in cases of  disease and morbidity  of the heart, so in order to identify the effect of changing the Doppler frequency on the speed of blood flow and the relationship of

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