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Data Driven Approach for Predicting Pore Pressure of Oil and Gas Wells, Case Study of Iraq Southern Oilfields
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Precise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables are vertical depth, bulk density, and acoustic compressional wave velocity, with the activation function of tangent sigmoid. The average percent error, absolute average percent error, mean square error, root mean square error, and correlation coefficient (R2) were applied for evaluation. The results revealed that the best artificial neural network structure was (3-8-1), with average percent error, absolute average percent error, mean square error, root mean square error, and correlation coefficient R2 of -0.52, 1.01, 3994, 63.2, and 0.995, respectively. A C++ computer program is provided with a calculation sample to simplify the implementation of the proposed artificial neural network. The dependency degree of pore pressure on each input parameter is investigated, revealing the highest impact of depth on pore pressure prediction. Furthermore, to check the validity of the artificial neural network against the different datasets, the artificial neural network performance was compared with 84 new data points and showed an advantage over the existing models. The very good performance of artificial neural network for different types of oil reservoirs and formations reveals an insignificant effect of lithology on the prediction of pore pressure.  

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Publication Date
Sun Jan 01 2023
Journal Name
E3s Web Of Conferences
Assessments and Historical Changes the Water Quality of Sawa Lake, Southern Iraq for the Period 1977-2020
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This investigation pertains to the evaluation of water quality in SAWA Lake, located in the Al-Muthanna province of Southern Iraq, from 1977 to 2020. Understanding the water quality and assessments of this Lake is of great importance. The Lake is home to small, transparent, blind fish measuring approximately 10 cm and is often referred to as the "wonderful" or "strange" Lake due to its many unique features. The study focuses on several elements to represent water quality, including total dissolved solids (TDS), electrical conductivity (EC), pH, and temperature (T), which were measured directly in the field. Additionally, scientific concepts such as K+, Ca2+, Cl-, HCO

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Publication Date
Fri Jul 17 2026
Journal Name
Journal Of Engineering
Stratified Water-Oil-Gas Flow Through Horizontal Pipes
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Publication Date
Sun Dec 01 2024
Journal Name
Journal Of Economics And Administrative Sciences
Nadaraya-Watson Estimation of a Circular Regression Model on Peak Systolic Blood Pressure Data
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Purpose: The research aims to estimate models representing phenomena that follow the logic of circular (angular) data, accounting for the 24-hour periodicity in measurement. Theoretical framework: The regression model is developed to account for the periodic nature of the circular scale, considering the periodicity in the dependent variable y, the explanatory variables x, or both. Design/methodology/approach: Two estimation methods were applied: a parametric model, represented by the Simple Circular Regression (SCR) model, and a nonparametric model, represented by the Nadaraya-Watson Circular Regression (NW) model. The analysis used real data from 50 patients at Al-Kindi Teaching Hospital in Baghdad. Findings: The Mean Circular Erro

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Publication Date
Tue Dec 31 2019
Journal Name
Journal Of Engineering
A High Resolution 3D Geomodel for Giant Carbonate Reservoir- A Field Case Study from an Iraqi Oil Field
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Constructing a fine 3D geomodel for complex giant reservoir is a crucial task for hydrocarbon volume assessment and guiding for optimal development. The case under study is Mishrif reservoir of Halfaya oil field, which is an Iraqi giant carbonate reservoir. Mishrif mainly consists of limestone rocks which belong to Late Cenomanian age. The average gross thickness of formation is about 400m. In this paper, a high-resolution 3D geological model has been built using Petrel software that can be utilized as input for dynamic simulation. The model is constructed based on geological, geophysical, pertophysical and engineering data from about 60 available wells to characterize the structural, stratigraphic, and properties distribution along

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Publication Date
Tue Dec 31 2019
Journal Name
Journal Of Engineering
A High Resolution 3D Geomodel for Giant Carbonate Reservoir- A Field Case Study from an Iraqi Oil Field
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Constructing a fine 3D geomodel for complex giant reservoir is a crucial task for hydrocarbon volume assessment and guiding for optimal development. The case under study is Mishrif reservoir of Halfaya oil field, which is an Iraqi giant carbonate reservoir. Mishrif mainly consists of limestone rocks which belong to Late Cenomanian age. The average gross thickness of formation is about 400m. In this paper, a high-resolution 3D geological model has been built using Petrel software that can be utilized as input for dynamic simulation. The model is constructed based on geological, geophysical, pertophysical and engineering data from about 60 available wells to characterize the structural, stratigraphic, and properties distri

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Publication Date
Sun Oct 27 2024
Journal Name
Journal Of Economics And Administrative Sciences
An Integrated Approach to Constraints Theory and Fuzzy Analytical Hierarchy Process (FAHP) in Construction Projects (Case Study)
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The research endeavors to harness the benefits stemming from the integration of constraint theory into construction project management, with the primary goal of mitigating project completion delays. Additionally, it employs fuzzy analysis to determine the relative significance of fundamental constraints within projects by assigning them appropriate weights. The research problem primarily revolves around two key issues. Firstly, the persistent utilization of outdated methodologies and a heavy reliance on workforce experience without embracing modern computerized technologies. Secondly, the recurring problem of project delivery delays. Construction projects typically encompass five fundamental constraint types: cost restrictions, tim

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Exploring Important Factors in Predicting Heart Disease Based on Ensemble- Extra Feature Selection Approach
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Heart disease is a significant and impactful health condition that ranks as the leading cause of death in many countries. In order to aid physicians in diagnosing cardiovascular diseases, clinical datasets are available for reference. However, with the rise of big data and medical datasets, it has become increasingly challenging for medical practitioners to accurately predict heart disease due to the abundance of unrelated and redundant features that hinder computational complexity and accuracy. As such, this study aims to identify the most discriminative features within high-dimensional datasets while minimizing complexity and improving accuracy through an Extra Tree feature selection based technique. The work study assesses the efficac

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Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Engineering
The use of Prepared Zeolite Y from Iraqi kaolin for Fluid Catalytic Cracking of Vacuum Gas Oil
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The faujasite type Y zeolite catalyst was prepared from locally available kaolin. For prepared faujasite type NaY zeolite X-ray, FT-IR, BET pore volume and surface area, and silica/ alumina were determined. The Xray and FT-IR show the compatibility of prepared catalyst with the general structure of standard zeolite Y. BET test shows that the surface area and pore volume of prepared catalyst were 360 m2 /g and 0.39 cm3 /g respectively.
The prepared faujasite type NaY zeolite modified by exchanging sodium ion with ammonium ion using ammonium nitrate and then ammonium ion converted to hydrogen ion. The maximum sodium ion exchange with ammonium ion was 53.6%. The catalytic activity of prepared faujasite type NaY, NaNH4Y and NaHY zeolites

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Publication Date
Mon Feb 16 2026
Journal Name
Agribusiness
Economic Analysis of AI‐Driven Resource Efficiency in Sustainable Agriculture in Iraq
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Abstract<p> Water scarcity, rising energy costs, and declining irrigation efficiency are significant barriers to wheat production in Iraq. This study evaluates the economic, environmental, and sustainability impacts of integrating artificial intelligence (AI) into irrigation management under semiarid conditions. Field experiments conducted at the Al‐Ra'id Research Station in Baghdad during the 2025 season compared conventional diesel‐based irrigation with AI‐assisted irrigation that used soil moisture sensors, Internet of Things (IoT) controllers, and predictive weather algorithms. The analysis employed Cobb–Douglas production modeling, cost–benefit analysis, net</p> ... Show More
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Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
A study of the physical and chemical characteristics of the waters of the central marshes in southern Iraq after restoration
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some ecological (physical and chemical varible) of water samples were studies monthly from December 2008 to May 2009 at two stations( St.1) Al - Chibayesh marsh and (St.2) Abu – Zirik marsh which are located in the south of Iraq . These variables included : Temperature, pH, EC, Dissolved oxygen , Total alkalinity, Nitrate, Sulphate, and phosphate, Si-SiO2 and Ca ,Mg, Cl, The marsh Considered as fresh water and alkaline. Abu-Zirik less than Al-Chibayesh.

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