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Using Artificial Neural Network to Predict Rate of Penetration from Dynamic Elastic Properties in Nasiriya Oil Field
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   The time spent in drilling ahead is usually a significant portion of total well cost. Drilling is an expensive operation including the cost of equipment and material used during the penetration of rock plus crew efforts in order to finish the well without serious problems. Knowing the rate of penetration should help in speculation of the cost and lead to optimize drilling outgoings. Ten wells in the Nasiriya oil field have been selected based on the availability of the data. Dynamic elastic properties of Mishrif formation in the selected wells were determined by using Interactive Petrophysics (IP V3.5) software based on the las files and log record provided. The average rate of penetration and average dynamic elastic properties for the studied wells was determined and listed with depth. Laboratory measurements were conducted on core samples selected from two wells from the studied wells. Ultrasonic device was used to measure the transit time of compressional and shear waves and to compare these results with log records. The reason behind that is to check the accuracy of the Greenberg-Castagna equation that was used to estimate the shear wave in order to calculate dynamic elastic properties. The model was built using Artificial Neural Network (ANN) to predict the rate of penetration in Mishrif formation in the Nasiriya oil field for the selected wells. The results obtained from the model were compared with the provided rate of penetration from the field and the Mean Square Error (MSE) of the model was 3.58 *10-5.

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Publication Date
Mon Jan 01 2024
Journal Name
Explainable Artificial Intelligence In The Digital Sustainability Administration
Artificial Intelligence and Trends Using in Sustainability Audit: A Bibliometric Analysis
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Publication Date
Thu Jun 23 2022
Journal Name
American Scientific Research Journal For Engineering, Technology, And Sciences
A Review of TCP Congestion Control Using Artificial Intelligence in 4G and 5G Networks
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In recent years, the field of research around the congestion problem of 4G and 5G networks has grown, especially those based on artificial intelligence (AI). Although 4G with LTE is seen as a mature technology, there is a continuous improvement in the infrastructure that led to the emergence of 5G networks. As a result of the large services provided in industries, Internet of Things (IoT) applications and smart cities, which have a large amount of exchanged data, a large number of connected devices per area, and high data rates, have brought their own problems and challenges, especially the problem of congestion. In this context, artificial intelligence (AI) models can be considered as one of the main techniques that can be used to solve ne

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Using Different Types of Projectiles to Make Avalanches to Avoid Human Being Disasters and Properties Destruction
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Some geological phenomena as landslides and the mobilization of the accumulated rocks or soil are discussed in this research by using projectiles that cause mobility and falling of these land masses which are present at the top of mountains and edges of roads and streets to avoid accidents and human disasters which will occur if they are left falling by effect of climate or vibrating factors that are produced by performing dams, bridges and reservoirs. According to the different divisions of land masses groups, primary and secondary, which depend on type of movement and material arrangement that form the mobile masses, this research had shown the effect of projectiles for every type of cannons on the mobility of every groups of these rocks

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Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Geological Journal
Biostratigraphy of the Late Cretaceous-Early Paleocene Succession in Selected Wells, Jambur Oil field, Kirkuk, Northern Iraq
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The Late Cretaceous-Early Paleocene Shiranish and Aliji formations have been studied in three selected wells in Jambur Oil Field (Ja-50, Ja-53, and Ja-67) in Kirkuk, Northeastern Iraq. This study included lithostratigraphy and biostratigraphy. The Late Campanian-Maastrichtian Shiranish Formation consist mainly of thin marly and chalky limestone beds overlain by thin marl beds, with some beds of marly limestone representing an outer shelf basinal environment, the unconformable contact with the above Middle Paleocene-Early Eocene Aliji Formation contain layers of limestone with marly limestone and chalky limestone which represents an outer shelf basinal environment. Five Biozones in the Shiranish Formation were determined which are: 1

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Publication Date
Sat Feb 01 2020
Journal Name
Journal Of Economics And Administrative Sciences
Effect of Job Burnout on Employee Performance: Field Research in the General Company for Vegetable Oil Industry
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Abstract

      This research aims to know the effect of job burnout in the worker’s performance. The researcher presented a theoretical basis for job burnout and the worker's performance. In order to achieve the objectives of the research, a hypothesis was drawn up that determines the nature of the relationship between the independent variable of job burnout and its dimensions (reduced personal accomplishment, depersonalization, Emotional Exhaustion) and variable dependent performance of workers dimensions (productivity, job satisfaction, organizational commitment, creativity), And to represent the volume of this community according to (de Morgan, D. Morgan) glo

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Publication Date
Sat Mar 30 2024
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Optimization of Separator Size and Operating Pressure for Three-phase Separators in the West Qurna1 Oil Field
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An optimization study was conducted to determine the optimal operating pressure for the oil and gas separation vessels in the West Qurna 1 oil field. The ASPEN HYSYS software was employed as an effective tool to analyze the optimal pressure for the second and third-stage separators while maintaining a constant operating pressure for the first stage. The analysis involved 10 cases for each separation stage, revealing that the operating pressure of 3.0 Kg/cm2 and 0.7 Kg/cm2 for the second and third stages, respectively, yielded the optimum oil recovery to the flow tank. These pressure set points were selected based on serval factors including API gravity, oil formation volume factor, and gas-oil ratio from the flow tank.    To impro

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Publication Date
Mon Mar 31 2025
Journal Name
The Iraqi Geological Journal
Evaluation of Machine Learning Techniques for Missing Well Log Data in Buzurgan Oil Field: A Case Study
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The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti

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Publication Date
Thu Jun 29 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of Hydraulic Flow Units for Jeribe Reservoir in Jambour Oil Field Applying Flow Zone Indicator Method
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The Jeribe reservoir in the Jambour Oil Field is a complex and heterogeneous carbonate reservoir characterized by a wide range of permeability variations. Due to limited availability of core plugs in most wells, it becomes crucial to establish correlations between cored wells and apply them to uncored wells for predicting permeability. In recent years, the Flow Zone Indicator (FZI) approach has gained significant applicability for predicting hydraulic flow units (HFUs) and identifying rock types within the reservoir units.    This paper aims to develop a permeability model based on the principles of the Flow Zone Indicator. Analysis of core permeability versus core porosity plot and Reservoir Quality Index (RQI) - Normalized poros

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Publication Date
Sat Jan 01 2022
Journal Name
Materials Today: Proceedings
Investigating the elastic and plastic behavior of I-steel beams by using carbon fiber laminates
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Publication Date
Mon Jan 01 2024
Journal Name
Studies In Systems, Decision And Control
The Effect of Using an Accounting Information System Based on Artificial Intelligence in Detecting Earnings Management to Enhance the Sustainability of Economic Units
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This research aims to clarify the importance of an accounting information system that uses artificial intelligence to detect earnings manipulation. The research problem stems from the widespread manipulation of earning in economic entities, especially at the local level, exacerbated by the high financial and administrative corruption rates in Iraq due to fraudulent accounting practices. Since earning manipulation involves intentional fraudulent acts, it is necessary to implement preventive measures to detect and deter such practices. The main hypothesis of the research assumes that an accounting information system based on artificial intelligence cannot effectively detect the manipulation of profits in Iraqi economic entities. The researche

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