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.
Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a
... Show MoreIn many video and image processing applications, the frames are partitioned into blocks, which are extracted and processed sequentially. In this paper, we propose a fast algorithm for calculation of features of overlapping image blocks. We assume the features are projections of the block on separable 2D basis functions (usually orthogonal polynomials) where we benefit from the symmetry with respect to spatial variables. The main idea is based on a construction of auxiliary matrices that virtually extends the original image and makes it possible to avoid a time-consuming computation in loops. These matrices can be pre-calculated, stored and used repeatedly since they are independent of the image itself. We validated experimentally th
... Show MoreThe development of wireless sensor networks (WSNs) in the underwater environment leads to underwater WSN (UWSN). It has severe impact over the research field due to its extensive and real-time applications. However effective execution of underwater WSNs undergoes several problems. The main concern in the UWSN is sensor nodes’ energy depletion issue. Energy saving and maintaining quality of service (QoS) becomes highly essential for UWASN because of necessity of QoS application and confined sensor nodes (SNs). To overcome this problem, numerous prevailing methods like adaptive data forwarding techniques, QoS-based congestion control approaches, and various methods have been devised with maximum throughput and minimum network lifesp
... Show MoreHM Al-Dabbas, RA Azeez, AE Ali, Iraqi Journal of Science, 2023
Regression testing being expensive, requires optimization notion. Typically, the optimization of test cases results in selecting a reduced set or subset of test cases or prioritizing the test cases to detect potential faults at an earlier phase. Many former studies revealed the heuristic-dependent mechanism to attain optimality while reducing or prioritizing test cases. Nevertheless, those studies were deprived of systematic procedures to manage tied test cases issue. Moreover, evolutionary algorithms such as the genetic process often help in depleting test cases, together with a concurrent decrease in computational runtime. However, when examining the fault detection capacity along with other parameters, is required, the method falls sh
... Show MoreJava is a high-level , third generation programming language were introduced Javaoptics Open Source Physics (OSP) as a new simulation for design one of the most important interference optical coating called antireflection coating. It is recent developments in deign thin-film coatings. (OSP) shows multiple beam interferences from a parallel dielectric thin film and the evolution of reflection factors. It is simple to use and efficiently also can serve educational purposes. The obtained results have been compared with needle method
Precision irrigation applications are used to optimize the use of water resources, by controlling plant water requirements through using different systems according to soil moisture and plant growth periods. In precision irrigation, different rates of irrigation water are applied to different places of the land in comparison with traditional irrigation methods. Thus the cost of irrigation water is reduced. As a result of the fact that precise irrigation can be used and applied in all irrigation systems, it spreads rapidly in all irrigation systems. The purpose of the Precision Agriculture Technology System (precision irrigation) , is to apply the required level of irrigation according to agricultural inputs to the specified location , by us
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