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

The paper generates a geological model of a giant Middle East oil reservoir, the model constructed based on the field data of 161 wells. The main aim of the paper was to recognize the value of the reservoir to investigate the feasibility of working on the reservoir modeling prior to the final decision of the investment for further development of this oilfield. Well log, deviation survey, 2D/3D interpreted seismic structural maps, facies, and core test were utilized to construct the developed geological model based on comprehensive interpretation and correlation processes using the PETREL platform. The geological model mainly aims to estimate stock-tank oil initially in place of the reservoir. In addition, three scenarios were applie

With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se

Classifying an overlapping object is one of the main challenges faced by researchers who work in object detection and recognition. Most of the available algorithms that have been developed are only able to classify or recognize objects which are either individually separated from each other or a single object in a scene(s), but not overlapping kitchen utensil objects. In this project, Faster R-CNN and YOLOv5 algorithms were proposed to detect and classify an overlapping object in a kitchen area.  The YOLOv5 and Faster R-CNN were applied to overlapping objects where the filter or kernel that are expected to be able to separate the overlapping object in the dedicated layer of applying models. A kitchen utensil benchmark image database and

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 g

The synthesis of the bisaldehyde ligand 2-(1,1-dimethyl-1,3-dihydro-2H-benzo[e]indol-2-ylidene)malonaldehyde (B) and its coordinated compounds with Cr(III), Mn(II), Fe(II), Co(II), Ni(II) and Cu(II) ions are reported. The synthetic route of B was completed by adopting the Vilsmeier-Haack reaction. This was based on the mixing of 1,1,2-trimethyl-1H-benzo[e]indole with phosphoryl trichloride and N, N-dimethylformamide (anhydrous) that gave the aminomethylenemalondialdehyde. The use of POCl3 and DMF was aimed to give the Vilsmeier-Haack intermediate, which was kept at 5°C and then heated with stirring at 85°C. The addition of an aqueous NaOH solution (35%) to the reaction mixture resulted in the isolation of B. The monomeric coordinated comp

This study reports the formation, characterisation and biological evaluation of a Schiff base ligand and its corresponding metal complexes. The Schiff base ligand (HL) was prepared through a condensation reaction involving isonicotinohydrazide and N'-((1R,2R,4R,5S, E)-2,4-bis(4-chlorophenyl)-3-azabi cyclo[3.3.1]nonan-9-ylidene) isonicotinohydrazide (M) in EtOH solvent and (3-5) drops of conc. HCl. The interaction of HL with selected metal chlorides including Mn(+2), Co(+2), Ni(+2), Cu(+2) and Zn(+2) in a 2:1 (L:M) mole ratio resulted in the synthesis of complexes with the general formula [M(HL)Cl2] (where: M = Mn(+2),Co(+2) and Ni(+2)) and [M`(HL)Cl2] (where M` =  Cu(+2) and Zn(+2)). The characterisation of the prepared compounds w