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Numerical Simulation of Gas Lift Optimization Using Artificial Intelligence for a Middle Eastern Oil Field
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Abstract<p>Artificial lift techniques are a highly effective solution to aid the deterioration of the production especially for mature oil fields, gas lift is one of the oldest and most applied artificial lift methods especially for large oil fields, the gas that is required for injection is quite scarce and expensive resource, optimally allocating the injection rate in each well is a high importance task and not easily applicable. Conventional methods faced some major problems in solving this problem in a network with large number of wells, multi-constrains, multi-objectives, and limited amount of gas. This paper focuses on utilizing the Genetic Algorithm (GA) as a gas lift optimization algorithm to tackle the challenging task of optimally allocating the gas lift injection rate through numerical modeling and simulation studies to maximize the oil production of a Middle Eastern oil field with 20 production wells with limited amount of gas to be injected. The key objective of this study is to assess the performance of the wells of the field after applying gas lift as an artificial lift method and applying the genetic algorithm as an optimization algorithm while comparing the results of the network to the case of artificially lifted wells by utilizing ESP pumps to the network and to have a more accurate view on the practicability of applying the gas lift optimization technique. The comparison is based on different measures and sensitivity studies, reservoir pressure, and water cut sensitivity analysis are applied to allow the assessment of the performance of the wells in the network throughout the life of the field. To have a full and insight view an economic study and comparison was applied in this study to estimate the benefits of applying the gas lift method and the GA optimization technique while comparing the results to the case of the ESP pumps and the case of naturally flowing wells. The gas lift technique proved to have the ability to enhance the production of the oil field and the optimization process showed quite an enhancement in the task of maximizing the oil production rate while using the same amount of gas to be injected in the each well, the sensitivity analysis showed that the gas lift method is comparable to the other artificial lift method and it have an upper hand in handling the reservoir pressure reduction, and economically CAPEX of the gas lift were calculated to be able to assess the time to reach a profitable income by comparing the results of OPEX of gas lift the technique showed a profitable income higher than the cases of naturally flowing wells and the ESP pumps lifted wells. Additionally, the paper illustrated the genetic algorithm (GA) optimization model in a way that allowed it to be followed as a guide for the task of optimizing the gas injection rate for a network with a large number of wells and limited amount of gas to be injected.</p>
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Publication Date
Mon Feb 18 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Auditing Quality According To Artificial Intelligence: Applied Research on A Sample of Regulatory Bodies Working In The Federal Board of Supreme Audit
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The Evolution Of Information Technology And The Use Of Computer Systems Led To Increase Attention To The Use Of Modern Techniques In The Auditing Process , As It Will Overcome Some Of The Human Shortcomings In The Exercise Of Professional Judgment, Then It Can Improve The Efficiency And Effectiveness Of The Audit Process, Where The New Audit Methodologies Espouse The Concept Of Risk Which Includes Strategic Dimension With Regard To The Capacity Of The Entity To Achieve Its Goals, Which Requires Auditors To Rely On Advanced Technology That Can Identify The Factors Which Prevent The Entity From Achieving Its Objectives. The Idea Of Research Is To Preparing An Electronic Program Fer All Audit Work From Planning Through Sampling And Document

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Publication Date
Tue Mar 20 2018
Journal Name
Day 2 Wed, March 21, 2018
Numerical Approach for the Prediction of Formation and Hydraulic Fracture Properties Considering Elliptical Flow Regime in Tight Gas Reservoirs
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Abstract<p>As tight gas reservoirs (TGRs) become more significant to the future of the gas industry, investigation into the best methods for the evaluation of field performance is critical. While hydraulic fractured well in TRGs are proven to be most viable options for economic recovery of gas, the interpretation of pressure transient or well test data from hydraulic fractured well in TGRs for the accurate estimation of important reservoirs and fracture properties (e.g. fracture length, fracture conductivity, skin and reservoir permeability) is rather very complex and difficult because of the existence of multiple flow profiles/regimes. The flow regimes are complex in TGRs due to the large hydraulic fractures n</p> ... Show More
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Publication Date
Thu Jun 30 2011
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
CORRELATION FOR SOLUTION GAS -OIL RATIO OF IRAQI OILS AT PRESSURES BELOW THE BUBBLE POINT PRESSURE
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The solution gas-oil ratio is an important measurement in reservoir engineering calculations. The correlations are used when experimental PVT data from particular field are missing. Additional advantages of the correlations are saving of cost and time.
This paper proposes a correlation to calculate the solution gas -oil ratio at pressures below bubble point pressure. It was obtained by multiple linear regression analysis of PVT data collected from many Iraqi fields.
In this study, the solution gas-oil ratio was taken as a function of bubble point pressure, stock tank oil gravity, reservoir pressure, reservoir temperature and relative gas density.
The construction of the new correlation is depending on thirty seven PVT reports th

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Publication Date
Fri Sep 30 2011
Journal Name
Al-khwarizmi Engineering Journal
Composition and Temperature Dependence of Excess Volume of Heavy Oil-Stocks Mixtures + (Gas oil or Toluene or Reformate)
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Binary mixtures of three, heavy oil-stocks was subjected to density measurements at temperatures of 30, 35 and 40 °C. and precise data was acquired on the volumetric behavior of these systems. The results are reported in terms of equations for excess specific volumes of mixtures. The heavy oil-stocks used were of good varity, namely 40 stock, 60 stock, and 150 stock. The lightest one is 40 stock with °API gravity 33.69 while 60 stock is a middle type and 150 stock is a heavy one, with °API gravity 27.74 and 23.79 respectively. Temperatures in the range of 30-40 °C have a minor effect on excess volume of heavy oil-stock binary mixture thus, insignificant expansion or shrinkage is observed by increasing the temperature this effect beco

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Publication Date
Sat Dec 31 2022
Journal Name
Mathematical Modelling Of Engineering Problems
Experimental and Numerical Study of Open Channel Flow with T-Section Artificial Bed Roughness
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Experimental and numerical studies have been conducted on the effects of bed roughness elements such as cubic and T-section elements that are regularly half-channel arrayed on one side of the river on turbulent flow characteristics and bed erosion downstream of the roughness elements. The experimental study has been done for two types of bed roughness elements (cubic and T-section shape) to study the effect of these elements on the velocity profile downstream the elements with respect to different water flow discharges and water depths. A comparison between the cubic and T-section artificial bed roughness showed that the velocity profile downstream the T-section increased in smooth side from the river and decrease in the rough side

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Publication Date
Fri Mar 01 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The Relationship Between Competitive Intelligence and Entrepreneurial Performance By Centralizing Strategic Vigilance: Field study of a sample of National colleges in Iraq
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The aim of this study is to highlight the relationship between competitive intelligence and Entrepreneurial Performance by centralizing the strategic vigilance of a sample of civil faculties in Baghdad. The sample of the study was targeted at 10 Iraqi civil colleges, which consisted of (133) members of the faculty council of the faculties, the search data was collected using the questionnaire form as the main research tool. The results showed that the correlation and influence of competitive intelligence and strategic vigilance in the Entrepreneurial Performance, as well as the role of strategic vigilance as an intermediate variable between competitive intelligence and Entrepreneurial Performance.

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Publication Date
Sun Dec 31 2023
Journal Name
Iraqi Geological Journal
Advanced Geostatistical Techniques for Building 3D Geological Modeling: A Case Study from Cretaceous Reservoir in Bai Hassan Oil Field
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A 3D Geological model was generated using an advanced geostatistical method for the Cretaceous reservoir in the Bai Hassan oil field. In this study, a 3D geological model was built based on data from four wells for the petrophysical property distribution of permeability, porosity, water saturation, and NTG by using Petrel 2021 software. The geological model was divided into a structural model and a property model. The geological structures of the cretaceous reservoir in the Bai Hassan oil field represent elongated anticline folds with two faults, which had been clarified in the 3D Structural model. Thirteen formations represent the Cretaceous reservoir which includes (Shiranish, Mashurah, U.kometan, Kometan Shale, L. Kometan, Gulnen

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Publication Date
Wed Jul 01 2020
Journal Name
Journal Of Engineering
Permeability Determination of Tertiary Reservoir/Ajeel Oil Field
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This paper discusses the method for determining the permeability values of Tertiary Reservoir in Ajeel field (Jeribe, dhiban, Euphrates) units and this study is very important to determine the permeability values that it is needed to detect the economic value of oil in Tertiary Formation. This study based on core data from nine wells and log data from twelve wells. The wells are AJ-1, AJ-4, AJ-6, AJ-7, AJ-10, AJ-12, AJ-13, AJ-14, AJ-15, AJ-22, AJ-25, and AJ-54, but we have chosen three wells (AJ4, AJ6, and AJ10) to study in this paper. Three methods are used for this work and this study indicates that one of the best way of obtaining permeability is the Neural network method because the values of permeability obtained be

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Publication Date
Mon Nov 11 2019
Journal Name
Spe
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 parame</p> ... Show More
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Publication Date
Wed Mar 20 2024
Journal Name
Journal Of Petroleum Research And Studies
Advanced Machine Learning application for Permeability Prediction for (M) Formation in an Iraqi Oil Field
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Permeability estimation is a vital step in reservoir engineering due to its effect on reservoir's characterization, planning for perforations, and economic efficiency of the reservoirs. The core and well-logging data are the main sources of permeability measuring and calculating respectively. There are multiple methods to predict permeability such as classic, empirical, and geostatistical methods. In this research, two statistical approaches have been applied and compared for permeability prediction: Multiple Linear Regression and Random Forest, given the (M) reservoir interval in the (BH) Oil Field in the northern part of Iraq. The dataset was separated into two subsets: Training and Testing in order to cross-validate the accuracy

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