Horizontal wells have revolutionized hydrocarbon production by enhancing recovery efficiency and reducing environmental impact. This paper presents an enhanced Black Oil Model simulator, written in Visual Basic, for three-dimensional two-phase (oil and water) flow through porous media. Unlike most existing tools, this simulator is customized for horizontal well modeling and calibrated using extensive historical data from the South Rumaila Oilfield, Iraq. The simulator first achieves a strong match with historical pressure data (1954–2004) using vertical wells, with an average deviation of less than 5% from observed pressures, and is then applied to forecast the performance of hypothetical horizontal wells (2008–2011). The results validate the simulator’s reliability in estimating bottom-hole pressure (e.g., ±3% accuracy for HRU1 well) and water–oil ratios (e.g., WOR reduction of 15% when increasing horizontal well length from 1000 m to 2000 m). Notably, the simulator demonstrated that doubling the horizontal well length reduced WOR by 15% while increasing bottom-hole pressure by only 2%, highlighting the efficiency of longer wells in mitigating water encroachment. This work contributes to improved reservoir management by enabling efficient well placement strategies and optimizing extraction planning, thereby promoting both economic and resource-efficient hydrocarbon recovery.
Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi
... Show MoreMachine 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 MoreThe purpose of this paper is to develop a hybrid conceptual model for building information modelling (BIM) adoption in facilities management (FM) through the integration of the technology task fit (TTF) and the unified theory of acceptance and use of technology (UTAUT) theories. The study also aims to identify the influence factors of BIM adoption and usage in FM and identify gaps in the existing literature and to provide a holistic picture of recent research in technology acceptance and adoption in the construction industry and FM sector.
A batch and flow injection (FI) spectrophotometric methods are described for the determination of barbituric acid in aqueous and urine samples. The method is based on the oxidative coupling reaction of barbituric acid with 4-aminoantipyrine and potassium iodate to form purple water soluble stable product at λ 510 nm. Good linearity for both methods was obtained ranging from 2 to 60 μg mL−1, 5–100 μg mL−1 for batch and FI techniques, respectively. The limit of detection (signal/noise = 3) of 0.45 μg mL−1 for batch method and 0.48 μg mL−1 for FI analysis was obtained. The proposed methods were applied successfully for the determination of barbituric acid in tap water, river water, and urine samples with good recoveries of 99.92
... Show MoreThis mixed method research analyses urban heritage and identity management concerning Karbala, and important spiritual and historical center. Homing in on particular spatial issues germane to Muharram’s rites, this study explores spiritual activities for the remembrance of the martyrdoms of Imam Hussein (A) and his brother Abbas (A), and their followers (RA), and identifies the way in which such activities construct urban identity in Karbala. Furthermore, this study contemplates the deployment of contemporary AR and VR technologies for urban identity. After reviewing extensive studies on religious, cultural, and urban heritage, a field survey of the Muharram pilgrimage in Karbala was conducted, spatially analyzing pilgrims’ movements in
... Show MoreThe research aims to identify how to enhance the quality of the human resources, focusing on four dimensions (efficiency, effectiveness, flexibility, and reliability), by adopting an adventure learning method that combines theoretical and applied aspects at the same time, when developing human resources and is applied using information technology, and that Through its dimensions, which are (cooperation, interaction, communication, and understanding), as the research problem indicated a clear deficiency in the cognitive perception of the mechanism of employing adventure learning dimensions in enhancing human resources quality, so the importance of research was to present treatments and proposals to reduce this problem. To achieve
... Show MorePersonalized Medicine represents a recent revolution in healthcare practice, focusing on tailoring different therapies to be precise for a specific individual; this is aided by exploring the number of genetic predispositions and lifestyle choices that fit each individual. In this article, the authors utilize and gather recent literature and opinions to discuss the impact of personalized medicine on chronic disease management and patient quality of life. Additional attention is paid to limits and possible ethical issues. Chronic diseases such as Hypertension, Diabetes, and chronic kidney diseases adversely affect multiple health indicators, including Quality of Life (QoL) and well-being. This will have additional impacts on physical
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