The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutting-edge machine learning techniques, our methodology shows a notable improvement in the precision and effectiveness of well-log predictions. Standard well logs from a reference well were used to train machine learning models. Additionally, conventional wireline logs were used as input to estimate facies for unclassified wells lacking core data. R-squared analysis and goodness-of-fit tests provide a numerical assessment of model performance, strengthening the validation process. The multi-resolution graph-based clustering and similarity threshold approaches have demonstrated notable results, achieving an accuracy of nearly 98%. Applying these techniques to data from eighteen wells produced precise results, demonstrating the effectiveness of our approach in enhancing the reliability and quality of well-log production.
This research concerns the fact of the school garden and how can we tackle this issue. The research starts with a question forwarded to those who are interested in the ministry of education matters; the question is that how is the extent of interest in the school garden project? And how it is activated in the Iraqi Educational Institution program? In addition, the analysis reveals the importance of the school garden since we, as teachers and students, suffer from seeing the view of the trashes, the wastes of school furniture, the stinking water and the weeds and how it is accumulated in the back yard of the school. To add fuel to the fire, the increase in number of the students; year after year. This increase leads to adding more classes
... Show MoreThis study aims to investigate the degree of practicing the motivated classroom evaluation environment for learning and its relationship to different feedback patterns. To achieve the objectives of the study, the correlational descriptive research design was employed. A questionnaire was constructed consisting of two parts: the classroom evaluation environment (13) items, and feedback patterns (24) items on a five-point scale. The psychometric properties of the questionnaire were verified in terms of validity and reliability. The questionnaire was applied to a sample of (265) male and female teachers who work in the second cycle schools for grades (5-10) of basic education in all academic majors in the Governorate of Muscat in the Sultan
... Show MoreThe consumption of fresh fruits has increased nowadays due to the lifestyle of the consumers. Maintaining the quality and nutritional value of cut fruits during storage is difficult compared to whole fruits. Deterioration of internal and external quality usually occurs in freshly harvested fruits. It is necessary to use different techniques to maintain the quality and increase the shelf life of the freshly cut product. This research studied the effect of treating apple slices with cold plasma once and with filtered water again on quality characteristics (hardness, moisture content, sugar content, carbohydrate content, and color) after being stored for five days. The best treatment was determined using two different pressures of the plasma j
... Show MorePurpose: The research aims to build an integrated knowledge framework for the basic research topic. The spirituality of the workplace is through access to the most important scientific proposals on these topics. In management thought framing, the knowledge within them in a serious attempt is to provide the appropriate answers about the intellectual dilemma of research by diagnosing the nature of the relationship with the influential elements and its historical development . Methodology: The study is relied on the analytical survey method. The research sample targeted (88) managers in the center of the Iraqi Ministry of Health exclusively from the researched senior leaders (general manager, assistant general manager, and head of department),
... Show MoreSecure storage of confidential medical information is critical to healthcare organizations seeking to protect patient's privacy and comply with regulatory requirements. This paper presents a new scheme for secure storage of medical data using Chaskey cryptography and blockchain technology. The system uses Chaskey encryption to ensure integrity and confidentiality of medical data, blockchain technology to provide a scalable and decentralized storage solution. The system also uses Bflow segmentation and vertical segmentation technologies to enhance scalability and manage the stored data. In addition, the system uses smart contracts to enforce access control policies and other security measures. The description of the system detailing and p
... Show MoreSignificant advances in the automated glaucoma detection techniques have been made through the employment of the Machine Learning (ML) and Deep Learning (DL) methods, an overview of which will be provided in this paper. What sets the current literature review apart is its exclusive focus on the aforementioned techniques for glaucoma detection using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines for filtering the selected papers. To achieve this, an advanced search was conducted in the Scopus database, specifically looking for research papers published in 2023, with the keywords "glaucoma detection", "machine learning", and "deep learning". Among the multiple found papers, the ones focusing
... Show MoreIn this paper, some commonly used hierarchical cluster techniques have been compared. A comparison was made between the agglomerative hierarchical clustering technique and the k-means technique, which includes the k-mean technique, the variant K-means technique, and the bisecting K-means, although the hierarchical cluster technique is considered to be one of the best clustering methods. It has a limited usage due to the time complexity. The results, which are calculated based on the analysis of the characteristics of the cluster algorithms and the nature of the data, showed that the bisecting K-means technique is the best compared to the rest of the other methods used.
This study develops a systematic density functional theory alongside on-site Coulomb interaction correction (DFT + U) and ab initio atomistic thermodynamics approachs for ternary (or mixed transitional metal oxides), expressed in three reservoirs. As a case study, among notable multiple metal oxides, synthesized CoCu2O3 exhibits favourable properties towards applications in solar, thermal and catalytic processes. This progressive contribution applies DFT + U and atomistic thermodynamic approaches to examine the structure and relative stability of CoCu2O3 surfaces. Twenty-five surfaces along the [001], [010], [100], [011], [101], [110] and [111] low-Miller-indices, with varying surface-termination configurations were selected in this study.
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