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 improve the robustness of forecasting production from smart wells using reservoir simulation. High-level details in the rock and fluid flow properties are required in the horizontal well region to capture the flow dynamics accurately. Thus, the study offers an enhanced method for predicting the performance of intelligent or smart wells in reservoir modeling. This model was history matched for a period of 20 years for three horizontal wells by using program Petrel (2017.4) and ECLIPS (2011). After successful validation of model on a field scale and well level, performance prediction was carried out to see the effect of (number of valves, number of nozzle and compartment length) using PICD/AFCV completion. Optimizing well performance entails lowering water-cut. From an economic viewpoint, the goal is to maximize NPV or profit, depending on the situation, from PICD wells, which compared to other wells.
Nowadays, cloud computing has attracted the attention of large companies due to its high potential, flexibility, and profitability in providing multi-sources of hardware and software to serve the connected users. Given the scale of modern data centers and the dynamic nature of their resource provisioning, we need effective scheduling techniques to manage these resources while satisfying both the cloud providers and cloud users goals. Task scheduling in cloud computing is considered as NP-hard problem which cannot be easily solved by classical optimization methods. Thus, both heuristic and meta-heuristic techniques have been utilized to provide optimal or near-optimal solutions within an acceptable time frame for such problems. In th
... Show MoreIn this research work, a simulator with time-domain visualizers and configurable parameters using a continuous time simulation approach with Matlab R2019a is presented for modeling and investigating the performance of optical fiber and free-space quantum channels as a part of a generic quantum key distribution system simulator. The modeled optical fiber quantum channel is characterized with a maximum allowable distance of 150 km with 0.2 dB/km at =1550nm. While, at =900nm and =830nm the attenuation values are 2 dB/km and 3 dB/km respectively. The modeled free space quantum channel is characterized at 0.1 dB/km at =860 nm with maximum allowable distance of 150 km also. The simulator was investigated in terms of the execution of the BB84 prot
... Show MoreExploring the B-Spline Transform for Estimating Lévy Process Parameters: Applications in Finance and Biomodeling Exploring the B-Spline Transform for Estimating Lévy Process Parameters: Applications in Finance and Biomodeling Letters in Biomathematics · Jul 7, 2025Letters in Biomathematics · Jul 7, 2025 Show publication This paper, presents the application of the B-spline transform as an effective and precise technique for estimating key parameters i.e., drift, volatility, and jump intensity for Lévy processes. Lévy processes are powerful tools for representing phenomena with continuous trends with abrupt changes. The proposed approach is validated through a simulated biological case study on animal migration in which movements are mo
... Show MoreEvolutionary algorithms are better than heuristic algorithms at finding protein complexes in protein-protein interaction networks (PPINs). Many of these algorithms depend on their standard frameworks, which are based on topology. Further, many of these algorithms have been exclusively examined on networks with only reliable interaction data. The main objective of this paper is to extend the design of the canonical and topological-based evolutionary algorithms suggested in the literature to cope with noisy PPINs. The design of the evolutionary algorithm is extended based on the functional domain of the proteins rather than on the topological domain of the PPIN. The gene ontology annotation in each molecular function, biological proce
... Show MoreThis paper studies the combination fluid viscous dampers in the outrigger system to add supplementary damping into the structure, which purpose to remove the dependability of the structure to lower variable intrinsic damping. It works by connecting the central core, comprising either shear walls or braced frames, to the outer perimeter columns.
The modal considered is a 36 storey square high rise reinforced concrete building. By constructing a discrete lumped mass model, and using frequency-based response function, two systems of dampers, parallel and series systems are studied. The maximum lateral load at the top of the building is calculated, and this load w
... Show MoreElectro-chemical Machining is significant process to remove metal with using anodic dissolution. Electro-chemical machining use to removed metal workpiece from (7025) aluminum alloy using Potassium chloride (KCl) solution .The tool used was made from copper. In this present the optimize processes input parameter use are( current, gap and electrolyte concentration) and surface roughness (Ra) as output .The experiments on electro-chemical machining with use current (30, 50, 70)A, gap (1.00, 1.25, 1.50) mm and electrolyte concentration (100, 200, 300) (g/L). The method (ANOVA) was used to limited the large influence factors affected on surface roughness and found the current was the large influence f
... Show MoreThis study is planned with the aim of constructing models that can be used to forecast trip production in the Al-Karada region in Baghdad city incorporating the socioeconomic features, through the use of various statistical approaches to the modeling of trip generation, such as artificial neural network (ANN) and multiple linear regression (MLR). The research region was split into 11 zones to accomplish the study aim. Forms were issued based on the needed sample size of 1,170. Only 1,050 forms with responses were received, giving a response rate of 89.74% for the research region. The collected data were processed using the ANN technique in MATLAB v20. The same database was utilized to