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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
Wed Jun 30 2021
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Effect of Temperature on Gas and Liquid Products Distribution in Thermal Cracking of Nigerian Bitumen
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The increasing population growth resulting in the tremendous increase in consumption of fuels, energy, and petrochemical products and coupled with the depletion in conventional crude oil reserves and production make it imperative for Nigeria to explore her bitumen reserves so as to meet her energy and petrochemicals needs. Samples of Agbabu bitumen were subjected to thermal cracking in a tubular steel reactor operated at 10 bar pressure to investigate the effect of temperature on the cracking reaction. The gas produced was analyzed in a Gas Chromatograph while the liquid products were subjected to Gas Chromatography-Mass Spectrometry (GC-MS) analysis. Heptane was the dominant gas produced in bitumen cracking at all temperatures and the r

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Publication Date
Tue Apr 02 2024
Journal Name
Iraqi Journal Of Applied Physics
Effect of Substrate Temperature on Characteristics and Gas Sensing Properties of Nb2O5/Si Thin Films
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Thin films of Nb2O5 have been successfully deposited using the DC reactive magnetron sputtering technique to manufacture NH3 gas sensors. These films have been annealed at a high temperature of 800°C for one hour. The assessment of the Nb2O5 thin films structural, morphological, and electrical characteristics was carried out using several methods such as X-ray diffraction (XRD), atomic force microscopy (AFM), energy-dispersive X-ray spectroscopy (EDS), Hall effect measurements, and sensitivity assessments. The XRD analysis confirms the polycrystalline composition of the Nb2O5 thin films with a hexagonal crystal structure. Furthermore, the sensitivity, response time, and recovery time of the gas sensor were evaluated for the Nb2O5 thin film

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Publication Date
Sun Jan 01 2023
Journal Name
Petroleum And Coal
Analyzing of Production Data Using Combination of empirical Methods and Advanced Analytical Techniques
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Publication Date
Thu Apr 21 2022
Journal Name
Journal Of Petroleum Research And Studies
Smart Well Modelling for As Reservoir in AG Oil Field
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Intelligent or smart completion wells vary from conventional wells. They have downhole flow control devices like Inflow Control Devices (ICD) and Interval Control Valves (ICV) to enhance reservoir management and control, optimizing hydrocarbon output and recovery. However, to explain their adoption and increase their economic return, a high level of justification is necessary. Smart horizontal wells also necessitate optimizing the number of valves, nozzles, and compartment length. A three-dimensional geological model of the As reservoir in AG oil field was used to see the influence of these factors on cumulative oil production and NPV. After creating the dynamic model for the As reservoir using the program Petrel (2017.4), we

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Publication Date
Sun Jun 30 2002
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
A Phase Behavior Compositional Model for Jambour Cretaceous Oil Reservoir
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Publication Date
Tue Sep 05 2023
Journal Name
Al-rafidain Journal Of Medical Sciences ( Issn 2789-3219 )
Protective Health Behaviors among Critical Care Nurses Concerning Pressure Ulcer Prevention for Hospitalized Patients at Baghdad Teaching Hospitals
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Background: Pressure ulcers remain a serious complication for immobile patients and a burden for healthcare professionals. Objectives: To assess health behavior prevention among critical care nurses regarding pressure ulcer prevention for hospitalized patients and to find out the relationship between critical care nurses health behavior prevention and sociodemographic variables. Methods: A cross-sectional design study was carried out in critical care units at three teaching hospitals. The study period extended from November 1, 2022, to January 28, 2023. Non-probability purposive sampling, whose target population was 100 nurses who work in critical care units in Baghdad, Iraq. The data were collected using a self-administered questio

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Publication Date
Sun Jul 01 2018
Journal Name
Journal Of Construction Engineering And Management
Measuring and Evaluating Safety Maturity of Construction Contractors: Multicriteria Decision-Making Approach
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Publication Date
Tue Mar 04 2014
Journal Name
International Journal Of Advanced Computing
User Authentication Approach using a Combination of Unigraph and Digraph Keystroke Features
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In Computer-based applications, there is a need for simple, low-cost devices for user authentication. Biometric authentication methods namely keystroke dynamics are being increasingly used to strengthen the commonly knowledge based method (example a password) effectively and cheaply for many types of applications. Due to the semi-independent nature of the typing behavior it is difficult to masquerade, making it useful as a biometric. In this paper, C4.5 approach is used to classify user as authenticated user or impostor by combining unigraph features (namely Dwell time (DT) and flight time (FT)) and digraph features (namely Up-Up Time (UUT) and Down-Down Time (DDT)). The results show that DT enhances the performance of digraph features by i

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Publication Date
Wed Jan 30 2019
Journal Name
Journal Of The College Of Education For Women
Iraq and Rockffler Institution for Charity 1929 – 1944
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The thirties and the early forties and the at end of the World War II of the last century
witnessed several attempts carried out by the Public Health Directorate and by the Iraqi
Ministry of Foreign Affairs to persuade the Rockefeller Foundation to fund Iraq with its
health program which is carried out in several regions in the world to promote the health and
social situations since Iraq during that period in history was badly in need to such plans and
programs because of this lack of financial and technical possibilities necessary for the
advancement of health and social dire situation.
The details of these attempts are deposited in the documents of the diplomatic mail
records of the United States of America , an

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Publication Date
Thu Jun 01 2023
Journal Name
Bulletin Of Electrical Engineering And Informatics
A missing data imputation method based on salp swarm algorithm for diabetes disease
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Most of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B

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