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Optimization of Fracture Parameters for Hydraulic Fractured Horizontal Well in a Heterogeneous Tight Reservoir: An Equivalent Homogeneous Modelling Approach
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Abstract<p>Building numerical reservoir simulation model with a view to model actual case requires enormous amount of data and information. Such modeling and simulation processes normally require lengthy time and different sets of field data and experimental tests that are usually very expensive. In addition, the availability, quality and accessibility of all necessary data are very limited, especially for the green field. The degree of complexities of such modelling increases significantly especially in the case of heterogeneous nature typically inherited in unconventional reservoirs. In this perspective, this study focuses on exploring the possibility of simplifying the numerical simulation process without compromising the accuracy of results for heterogeneous unconventional tight gas reservoir with an emphasis on optimisation of multi-stage hydraulic fractured parameters, such as fracture half-length and number of fractures towards maximization the net present value (NPV).</p><p>The key objectives of this study are to mitigate the effect of reservoir heterogeneity through building an equivalent simplified homogeneous reservoir simulation model for forecasting the production performance of fractured horizontal well in a heterogeneous carbonate tight gas reservoir and optimize the fracture parameters such as number of fractures and fracture half-length based on maximizing the NPV. The homogeneous model, which is equivalent to a heterogeneous reservoir model was built based on the statistical analysis of the rock properties of heterogeneous model. The simulation results obtained were analysed for a number of cases covering a range of fracture number (from 1 to 80), fracture half-length (from 500 to 2000 ft). The result demonstrated that the simplified equivalent homogeneous model has the ability to provide a good estimate for production forecasting, and determine the optimum number of fractures and fracture half-length within a high accuracy. The model is simple, yet provides good approximation with high accuracy, but save huge computation time.</p>
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Publication Date
Fri Apr 22 2022
Journal Name
Asian Journal Of Water, Environment And Pollution
An Ecological Comparison of Benthic Invertebrate Communities Between Sewage and Tigris River Water – Baghdad
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In the current study, two sites were selected from the city of Adhamiya, central Baghdad. The first site is the Adhamiya Corniche, which includes a sample of river water and the second includes domestic sewage in the same area. The total density of benthic invertebrates was 775 ind/m2, which is divided into 15 taxa. Biological indices were found, such as the stability index, the abundance index, the biodiversity index (Shannon’s index), the homogeneity index, and the invader’s guide. The result showed an increase in the density of benthic invertebrates, as well as an increase in the diversity of these organisms.

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Publication Date
Wed Sep 01 2021
Journal Name
Computers And Concrete
Improving the seismic performance of reinforced concrete frames using an innovative metallic-shear damper
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Publication Date
Thu Jul 21 2022
Journal Name
Energies
Dynamic Characteristics and Demonstration of an Integrated Linear Engine Generator with Alternative Electrical Machines
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A linear engine generator with a compact double-acting free piston mechanism allows for full integration of the combustion engine and generator, which provides an alternative chemical-to-electrical energy converter with a higher volumetric power density for the electrification of automobiles, trains, and ships. This paper aims to analyse the performance of the integrated engine with alternative permanent magnet linear tubular electrical machine topologies using a coupled dynamic model in Siemens Simcenter software. Two types of alternative generator configurations are compared, namely long translator-short stator and short translator-long stator linear machines. The dynamic models of the linear engine and linear generator, validated

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Publication Date
Tue Oct 08 2002
Journal Name
Iraqi Journal Of Laser
Laser Detection and Tracking System Using an Array of Photodiodes with Fuzzy Logic controller
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In this work laser detection and tracking system (LDTS) is designed and implemented using a fuzzy logic controller (FLC). A 5 mW He-Ne laser system and an array of nine PN photodiodes are used in the detection system. The FLC is simulated using MATLAB package and the result is stored in a lock up table to use it in the real time operation of the system. The results give a good system response in the target detection and tracking in the real time operation.

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Publication Date
Mon Jan 29 2024
Journal Name
Polymer Bulletin
An experimental study to investigate the effect of aluminum nanorod-reinforced epoxy matrix nanocomposites
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Publication Date
Fri Sep 15 2023
Journal Name
Journal Of Baghdad College Of Dentistry
Osseointegration effects of whey protein (histological and histomorphological observations): An experimental study on rabbits
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Background: Whey protein is the green-yellow colored, liquid portion of the milk, and it is also called the cheese serum, it is obtained after the separation of curd, during the coagulation of the milk. It contains a considerable amount of α-helix pattern with an evenly distributed hydrophobic and hydrophilic as well as basic and acidic amino acids along with their polypeptide chain. The major whey protein constituents include β-lactoglobulin (β-LG),α-lactalbumin (α-LA), immunoglobulins (IG), bovine serum albumin (BSA), bovine lactoperoxidase (LP), bovine lactoferrin (BLF) and minor amounts of a glycol macro peptide (GMP). Osseointegration can be defined as a process that is immune driven which leads to the formatio

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Publication Date
Sun Jan 01 2017
Journal Name
Journal Of Engineering
Performance Enhancement of an Air Cooled Air Conditioner with Evaporative Water Mist Pre-cooling
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The present paper deals with experimental investigation of the performance of air cooled split air conditioner, with evaporative water mist pre cooling to increase the cooling capacity and reduce the consumption power under hot and dry climate. This investigation considers how the performance can be enhanced by using water mist to pre-cool ambient air entering the condensers by adiabatic cooling process which depends on the ambient air wet bulb temperature; as well the condensing temperature and condensing pressure will be decreased accordingly. So the cooling capacity would be increased and consumption power would be decreased, consequently the energy ratio, EER would be improved. The performance of air cooled air conditioner with water

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Publication Date
Wed Jan 01 2014
Journal Name
International Journal Of Computer Applications
Mobile Position Estimation based on Three Angles of Arrival using an Interpolative Neural Network
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In this paper, the memorization capability of a multilayer interpolative neural network is exploited to estimate a mobile position based on three angles of arrival. The neural network is trained with ideal angles-position patterns distributed uniformly throughout the region. This approach is compared with two other analytical methods, the average-position method which relies on finding the average position of the vertices of the uncertainty triangular region and the optimal position method which relies on finding the nearest ideal angles-position pattern to the measured angles. Simulation results based on estimations of the mobile position of particles moving along a nonlinear path show that the interpolative neural network approach outperf

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Publication Date
Wed Apr 19 2017
Journal Name
Iraqi Dental Journal
Matching the Iris Color of Ocular Prosthesis Using an Eye Contact Lens: New Technique
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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
An Observation and Analysis the role of Convolutional Neural Network towards Lung Cancer Prediction
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Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c

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