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Evaluation of Gas and Downhole Water Sink-Assisted Gravity Drainage GDWS-AGD Process in Saturated Oil Reservoirs with Infinite-Acting Aquifer
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Abstract<p>A hybrid Gas-Enhanced and Downhole Water Sink-Assisted Gravity Drainage (GDWS-AGD) process has been suggested to enhance oil recovery by placing vertical injectors for CO2 at the top of the reservoir with a series of horizontal oil-producing and water-drainage wells located above and below the oil-water contact, respectively. The injected gas builds a gas cap that drives the oil to the (upper) oil-producing wells while the bottom water-drainage wells control water cresting. The hybrid process of GDWS-AGD process has been first developed and tested in vertical wells to minimize water cut in reservoirs with bottom water drive and strong water coning tendencies. The wells were dual-completed with 7-inch production casing and 2-3/8 inch tubings and perforated above the oil-water contact (OWC) for oil production and below OWC for water drainage. The two completions were hydraulically isolated inside the well by a packer. The bottom (water sink) completion drained water with a submersible pump.</p><p>The GDWS-AGD was efficiently adopted to improve oil recovery at the PUNQ saturated oil field. The PUNQ Field has an infinite active aquifer with very strong edge and bottom water drives. A black oil reservoir flow model was implemented for CO2 flooding simulation of the GDWS-AGD process in comparison with the Gas-Assisted Gravity Drainage (GAGD) process. The comparison was performed to obtain the clearest image about the performance of the combined GDWS-AGD process. Next, Design of Experiments (DoE) and proxy modeling were incorporated to find the most sensitive parameters that affect the GDWS-AGD process performance. The candidate parameters are porosity, horizontal and vertical permeability for each layer, radius of aquifer and rock compressibility.</p><p>In the GDWS-AGD, the produced water not only reduced water cut and coning, but also significantly reduced the reservoir pressure, resulting in improving gas injectivity. In addition, the GDWS-AGD process improved cumulative oil production. More specifically, the results showed that cumulative oil production increased from 3.8*105m3 to 4.7*105m3 and water cut decreased from 97% to 92% in all the horizontal oil producers. For the proxy model, it was cleared from Sobol analysis that the porosity for layer 5 was more influential parameter than others on cumulative oil through GDWS-AGD process with 31% main effects and 0.025% interaction effects, while the horizontal permeability for layer 4 was the most influential parameter with 24% main effects and 1.5% interaction effects. The novelty of GDWS-AGD process comes from its effectiveness to improve oil recovery with reducing the water coning, water cut, and improving gas injectivity. This leads to more economic implementation, especially with respect to the operational surface facilities.</p>
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Publication Date
Sat Mar 26 2016
Journal Name
Journal Of Materials Science: Materials In Electronics
Hydrothermal deposition of CdS on vertically aligned ZnO nanorods for photoelectrochemical solar cell application
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Publication Date
Mon Feb 01 2021
Journal Name
Iop Conference Series: Materials Science And Engineering
Azo Coupling Reaction for indirect Spectrophotometric Determination of Furosemide using Resorcinol as a Reagent
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Abstract<p>A simple and accurate method to determinate furosemide (FUR) based on converting the secondary amine to primary amine with acidic hydrolysis then azotization by nitrous acid and coupled with resorcinol as a coupling agent in aqueous medium at pH 13. The optical characteristic like beers law limit found to be (0.25-2.5) μg.ml<sup>−1</sup>, detection and quantification limits (0.0196) (0.0654) μg.ml<sup>−1</sup>respectivly and Sandel sensitivity was 0.006738 μg.cm<sup>−2</sup>. The least-square method was used to evaluate the regression equation and the correlation coefficient. The resulted azo dye has a maximum absorbance at 430 nm with light oran</p> ... Show More
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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Medicine And Life
An overview of neuro-ophthalmic disorders at Jenna Ophthalmic Center, Baghdad, Iraq (2021-2022)
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Neuro-ophthalmic disorders are often documented individually for each illness, with little data available on their overall incidence and pattern. The overall incidence of neuro-ophthalmic illnesses in Iraq is still not recorded. This study aimed to evaluate the clinical, demographic, and etiological features of patients seeking consultation at an Iraqi neuro-ophthalmology clinic. A prospective cross-sectional observational research was conducted at the Janna Ophthalmic Center in Baghdad, Iraq. The center serves a diverse patient population from various governorates. All newly diagnosed patients with neuro-ophthalmic disorders who visited the neuro-ophthalmological clinic, regardless of gender or age group, were included. The neuro-ophthalmo

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Publication Date
Sun Jun 01 2025
Journal Name
Journal Of Physics: Conference Series
Searching Ground State Properties of some Light Proton-Rich Nuclei Using Whittaker Wave Functions
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Abstract<p>In this work, the Whittaker wave functions were used to study the nuclear density distributions and elastic electron scattering charge form factors for proton-rich nuclei and their corresponding stable nuclei (<sup>10,8</sup>B, <sup>13,9</sup>C, <sup>14,12</sup>N and <sup>19,17</sup>F). The parameters of Whittaker’s basis were fixed to generate the experimental values of available size radii. The Whittaker basis was connected to harmonic-oscillator basis through boundary condition at match point. The nuclear shell model was opted with pure configuration for all studied nuclei to compute aforementioned studied quantities except <sup>10</sup></p> ... Show More
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Publication Date
Sat Jun 01 2024
Journal Name
Journal Of Ecological Engineering
Using Machine Learning Algorithms to Predict the Sweetness of Bananas at Different Drying Times
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Publication Date
Mon May 06 2024
Journal Name
Journal Of Ecological Engineering
Using Machine Learning Algorithms to Predict the Sweetness of Bananas at Different Drying Times
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The consumption of dried bananas has increased because they contain essential nutrients. In order to preserve bananas for a longer period, a drying process is carried out, which makes them a light snack that does not spoil quickly. On the other hand, machine learning algorithms can be used to predict the sweetness of dried bananas. The article aimed to study the effect of different drying times (6, 8, and 10 hours) using an air dryer on some physical and chemical characteristics of bananas, including CIE-L*a*b, water content, carbohydrates, and sweetness. Also predicting the sweetness of dried bananas based on the CIE-L*a*b ratios using machine learn- ing algorithms RF, SVM, LDA, KNN, and CART. The results showed that increasing the drying

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Publication Date
Thu Jan 13 2022
Journal Name
Medical &amp; Biological Engineering &amp; Computing
An integrated entropy-spatial framework for automatic gender recognition enhancement of emotion-based EEGs
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Publication Date
Tue Jan 01 2019
Journal Name
Journal Of Colloid And Interface Science
Organic acid concentration thresholds for ageing of carbonate minerals: Implications for CO2 trapping/storage
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Hypothesis CO2 geological storage (CGS) involves different mechanisms which can store millions of tonnes of CO2 per year in depleted hydrocarbon reservoirs and deep saline aquifers. But their storage capacity is influenced by the presence of different carboxylic compounds in the reservoir. These molecules strongly affect the water wetness of the rock, which has a dramatic impact on storage capacities and containment security. However, precise understanding of how these carboxylic acids influence the rock’s CO2-wettability is lacking. Experiments We thus systematically analysed these relationships as a function of pressure, temperature, storage depth and organic acid concentrations. A particular focus was on identifying organic acid conce

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Publication Date
Thu Apr 01 2021
Journal Name
Journal Of Engineering
Innovation Diffusion Elaboration into Architectural Movement
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The research investigates the term innovation and its role in elaborating architectural practice based on diffusion. The complexity of the architectural field compared with other fields shows a problem in explaining how innovations in architecture diffuse as a thought and act in a certain context of practice. Therefore, the research aims to build an intellectual model that explains the way personal thoughts resembled by unique models introduced by creative and innovator designers diffuse in a certain pattern elaborate these models into a state of prevailing thought resembled by the movement in architecture. The research will apply its model to the more comprehensive movement in architecture, which is the modern movement,

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Publication Date
Sat Jan 01 2011
Journal Name
Journal Of Engineering
FILTRATION MODELING USING ARTIFICIAL NEURAL NETWORK (ANN)
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In this research Artificial Neural Network (ANN) technique was applied to study the filtration process in water treatment. Eight models have been developed and tested using data from a pilot filtration plant, working under different process design criteria; influent turbidity, bed depth, grain size, filtration rate and running time (length of the filtration run), recording effluent turbidity and head losses. The ANN models were constructed for the prediction of different performance criteria in the filtration process: effluent turbidity, head losses and running time. The results indicate that it is quite possible to use artificial neural networks in predicting effluent turbidity, head losses and running time in the filtration process, wi

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