In many oil-recovery systems, relative permeabilities (kr) are essential flow factors that affect fluid dispersion and output from petroleum resources. Traditionally, taking rock samples from the reservoir and performing suitable laboratory studies is required to get these crucial reservoir properties. Despite the fact that kr is a function of fluid saturation, it is now well established that pore shape and distribution, absolute permeability, wettability, interfacial tension (IFT), and saturation history all influence kr values. These rock/fluid characteristics vary greatly from one reservoir region to the next, and it would be impossible to make kr measurements in all of them. The unsteady-state approach was used to calculate the relative permeability of five carbonate for core plugs from the Mishrif formation of WQ1. The relative permeability calculated by using Johnson, Bossler and Naumann (JBN) Correlation, which is, consider one of the unsteady-state approach where it found that the core plugs are water wet. A normalizing approach has been used to remove the effect of irreducible water and residual saturations, which would vary according on the environment. Based on their own irreducible water and trapped saturations, the relative permeabilities can subsequently be de-normalized and assigned to distinct sections (rock types) of the reservoir. The goal of this research is to normalize the relative permeability that was determined through water flooding.
The rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com
... Show MoreThe aim of this study is to estimate the parameters and reliability function for kumaraswamy distribution of this two positive parameter (a,b > 0), which is a continuous probability that has many characterstics with the beta distribution with extra advantages.
The shape of the function for this distribution and the most important characterstics are explained and estimated the two parameter (a,b) and the reliability function for this distribution by using the maximum likelihood method (MLE) and Bayes methods. simulation experiments are conducts to explain the behaviour of the estimation methods for different sizes depending on the mean squared error criterion the results show that the Bayes is bet
... Show MoreMersing is one of the places that have the potential for wind power development in Malaysia. Researchers often suggest it as an ideal place for generating electricity from wind power. However, before a location is chosen, several factors need to be considered. By analyzing the location ahead of time, resource waste can be avoided and maximum profitability to various parties can be realized. For this study, the focus is to identify the distribution of the wind speed of Mersing and to determine the optimal average of wind speed. This study is critical because the wind speed data for any region has its distribution. It changes daily and by season. Moreover, no determination has been made regarding selecting the average wind speed used for w
... Show MoreThe research aims to assess the claystone exposed in the Nfayil Formation (Middle Miocene) for Portland cement (P.C.) manufacturing based on mineralogy and geochemistry. The importance of the study is to avoid the miming of the agricultural soils that are mining now for the cement industry. Claystones of Nfayil Formation and the limestone of the Euphrates Formation were used to design the raw mixture as clay to limestone (1:3). The chemical composition (%) of the designed mixture was calculated using the Alligation Alternative Method (A.A.M.) as CaO (65.52), MgO (1.05), SiO2 (21.65), Al2O3 (7.43), Fe2O3 (2.62), Na2O3+K2O (1.52) and SO3 (0.26), which are suitable for P.C. The lime saturation factor (LSF = 92.8), silica saturation fac
... Show MoreThis study aims to explore the relationship between the degree of application of digital leadership and the development of administrative work at the University of Tabuk. It further aims to examine the presence of statistically significant differences between the average responses of faculty members and employees at the University of Tabuk regarding the study axes that are attributed to the following variables: (scientific rank, gender, and job), the study used the descriptive approach in its correlative style, and the questionnaire was used as a tool for data collection, as it was applied to a simple random of (310) members of the faculty and staff. University of Tabuk. The results showed that the degree of digital leadership applicatio
... Show MoreIn this study, the mobile phone traces concern an ephemeral event which represents important densities of people. This research aims to study city pulse and human mobility evolution that would be arise during specific event (Armada festival), by modelling and simulating human mobility of the observed region, depending on CDRs (Call Detail Records) data. The most pivot questions of this research are: Why human mobility studied? What are the human life patterns in the observed region inside Rouen city during Armada festival? How life patterns and individuals' mobility could be extracted for this region from mobile DB (CDRs)? The radius of gyration parameter has been applied to elaborate human life patterns with regards to (work, off) days for
... Show MoreIn this paper, integrated quantum neural network (QNN), which is a class of feedforward
neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that
... Show MoreGlobalisation and rapid environmental change have created many challenges for public and private organisations across Iraq as a developing country, particularly in the higher education sector. This includes, for example, decreases in government funding; increased demand for higher education; a need for economic transformation, and related competitiveness of organizations. Such challenges require exceptional leaders and strategic planning in order to take action to improve. In Iraq, the higher education sector is still one of the main foundations in progressing the knowledge economy. Studies into leadership style, strategic planning processes, and the importance of leadership and organisational culture to an organisation’s success have bee
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