A common field development task is the object of the present research by specifying the best location of new horizontal re-entry wells within AB unit of South Rumaila Oil Field. One of the key parameters in the success of a new well is the well location in the reservoir, especially when there are several wells are planned to be drilled from the existing wells. This paper demonstrates an application of neural network with reservoir simulation technique as decision tool. A fully trained predictive artificial feed forward neural network (FFNNW) with efficient selection of horizontal re-entry wells location in AB unit has been carried out with maintaining a reasonable accuracy. Sets of available input data were collected from the exploited grids and used in the training and testing of the used network. A comparison between the calculated and observed cumulative oil production has been carried out through the testing steps of the constructed ANN, an absolute average percentage error of the used network was reached to 4.044%, and this is consider to be an acceptable limit within engineering applications, in addition to that, a good behavior was reached with (FFNNW) and suitable re-entry wells location were identified according to the reservoir configuration (pressure and saturation distribution) output from SRF simulation model at the end of 2005.
The adsorption ability of Iraqi initiated calcined granulated montmorillonite to adsorb Symmetrical Schiff Base Ligand 4,4’-[hydrazine-1, 2-diylidenebis (methan-1-yl-1-ylidene)) bis (2-methoxyphenol)] derived from condensation reaction of hydrazine hydrate and 4-hydroxy-3-methoxybenzaldehyde, from aqueous solutions has been investigated through columnar method.The ligand (H2L) adsorption found to be dependent on adsorbent dosage, initial concentration and contact time.All columnar experiments were carried out at three different pH values (5.5, 7and 8) using buffer solutions at flow rate of (3 drops/ min.),at room temperature (25±2)°C. The experimental isotherm data were analyzed using Langmuir, Freundlich and Temkin equations. The monol
... Show MoreThe Co (II), Ni (II) ,Cu(II), Zn(II) ,Cd(II) and Hg(II) complexes of mixed of amino acid (L-Alanine ) and Trimethoprim antibiotic were synthesized. The complexes were characterized using melting point, conductivity measurement and determination the percentage of the metal in the complexes by flame (AAS). Magnetic susceptibility, Spectroscopic Method [FTIR and UV-Vis]. The general formula have been given for the prepared mixed ligand complexes [M(Ala)2(TMP)(H2O)] where L- alanine (abbreviated as (Ala ) = (C5H9NO2) deprotonated primary ligand, L- Alanine ion .= (C5H8NO2 -) Trimethoprim (abbreviated as (TMP ) = C10H11N3O3S M(II) = Co (II),Ni(II) ,Cu(II), Zn(II) ,Cd(II) and Hg(II). The results showed that the deprotonated L- Alanine by KOH (Ala
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New mixed ligand complexes of New Schiff base 4,4'- ((naphthalen-1-ylimino) methylene) dibenzene-1,3-diol and 8-hydroxy quinoline: Synthesis, Spectral Characterization, Thermal studies and Biological Activities
Comparison is the most common and effective technique for human thinking: the human mind always judges something new based on its comparison with similar things that are already known. Therefore, literary comparisons are always clear and convincing. In our daily lives, we are constantly forced to compare different things in terms of quantity, quality, or other aspects. It is known that comparisons are used in literature in order for speech to be clear and effective, but when these comparisons are used in everyday speech, it is in order to convey the meaning directly and quickly, because many of these expressions used daily are comparisons. In our research, we discussed this comparison as a means of metaphor and expression in Russia
... Show MoreThis work focuses on the preparation of pure nanocrystalline SnO2 and SnO2:Cu thin films on cleaned glass substrates utilizing a sol-gel spin coating and chemical bath deposition (CBD) procedures. The primary aim of this study is to investigate the possible use of these thin films in the context of gas sensor applications. The films underwent annealing in an air environment at a temperature of 500 ◦C for duration of 60 minutes. The thickness of the film that was deposited may be estimated to be around 300 nm. The investigation included an examination of the structural, optical, electrical, and sensing characteristics, which were explored across various preparation circumstances, specifically focusing on varied
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new six mixed ligand complexes of some transition metal ions Manganese (II), Cobalt(II), Iron (II), Nickel (II) , and non transition metal ion zinc (II) And Cadmium(II) with L-valine (Val H ) as a primary ligand and Saccharin (HSac) as a secondary ligands have been prepared. All the prepared complexes have been characterized by molar conductance, magnetic susceptibility infrared, electronic spectral, Elemental microanalysis (C.H.N) and AA . The complexes with the formulas [M(Val)2(HSac)2] M= Mn (II) , Fe (II) , Co(II) ,Ni(II), Cu (II),Zn(II) and Cd(II) L- Val H= (C5H11NO2) , C7H5NO3S The study shows that these complexes have octahedral geometry; The metal complexes have been screened for their in microbiological activities against bacteria.
... Show MoreThe syntheses, characterizations and structures of three novel dichloro(bis{2-[1-(4-methoxyphenyl)-1H-1,2,3-triazol-4-yl-κN3]pyridine-κN})metal(II), [M(L)2Cl2], complexes (metal = Mn, Co and Ni) are presented. In the solid state the molecules are arranged in infinite hydrogen-bonded 3D supramolecular structures, further stabilized by weak intermolecular π…π interactions. The DFT results for all the different spin states and isomers of dichloro(bis{2-[1-phenyl-1H-1,2,3-triazol-4-yl-κN3]pyridine-κN})metal(II) complexes, [M(L1)2Cl2], support experimental measurements, namely that (i) d5 [Mn(L1)2Cl2] is high spin with S = 5/2; (ii) d7 [Co(L1)2Cl2] has a spin state of S = 3/2, (iii) d8 [Ni(L1)2Cl2] has a spin state of S =
... Show MoreEarly detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med
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In this research, Artificial Neural Networks (ANNs) technique was applied in an attempt to predict the water levels and some of the water quality parameters at Tigris River in Wasit Government for five different sites. These predictions are useful in the planning, management, evaluation of the water resources in the area. Spatial data along a river system or area at different locations in a catchment area usually have missing measurements, hence an accurate prediction. model to fill these missing values is essential.
The selected sites for water quality data prediction were Sewera, Numania , Kut u/s, Kut d/s, Garaf observation sites. In these five sites models were built for prediction of the water level and water quality parameters.
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