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.
Low temperature and high relative humidity in the spring season led to decrease of field emergence ratio and growth in maize. Planting dates and seeds stimulation can be appropriate fix. Field experiment was conducted in the two spring seasons of 2022 and 2023. Randomize complete block design with split-plot arrangement and four replications was used. Planting date treatments (February 15th, March 1st and 15th and April 1st, 15th) were placed in main plots. Seeds stimulation treatments (potassium nitrate 6 mg L-1 + licorice extract 6 g L-1 as well as treatment of soaking with distilled water only) were placed in subplots. Seeds stimulation (potassium nitrate+licorice extract) or planting date of February 15th were superior at traits of fiel
... Show MoreBackground: Mouthwashes used widely as ancillary to mechanical oral hygiene methods. Little information provided about the effect of mouthwashes on ions released from orthodontic brackets. Therefore, the present study has been established to evaluate the effect of different mouthwashes on the corrosion resistance and the biocompatibility of two brands of brackets. Materials and Methods: Eighty premolar stainless steel brackets were used (40 brackets from each brand). They were subdivided into four subgroups (n=10) according to immersion media (deionized distilled water, Corsodyl, Listerine and Silca herb mouthwashes). Each bracket was stored in a closely packed glass tube filled with 15ml of the immersion media and incubated for 45 days at
... Show MoreThe aim of this investigation is to study and analysis the role of governance in the evaluation of the and social performance of the economic units to be addressed through the concept of corporate governance and then to the social performance and its relationship to corporate governance.
The most important obtained results from this research is that the corporate governance of extreme importance, and derive their importance from being an essential tool to contribute to the transparency and fair disclosure of the financial results of economic units in the fight against financial and administrative corruption in economic units, thus providing protection and confidence of all parties, and the evaluating soci
... Show MoreBackground: Wound healing is a complex dynamical interaction between various cell types, the extracellular matrix, cytokines, and growth factors. osteoponetin is a substance that acts as an anti-inflammatory. Aims of study: The study was designed to identify the role of local exogenous applications of osteopontin on wound healing (in cheek skin). Materials and methods: Thirty adult male albino rats weighting an average of (250-300gm) used in this study, incisional wounds were made in the skin of the cheek of rat and they were divided into the following groups: A-Control group: 15 rats treated with 1µ l of normal saline B-Experimental groups: 15 rats treated with topical application of 1µl osteopontin. The scarification of animals we
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The current research aims to identify the level of E-learning among middle school students, the level of academic passion among middle school students, and the correlation between e-learning and academic passion among middle school students. In order to achieve the objectives of the research, the researcher developed two questionnaires to measure the variables of the study (e-learning and study passion) among students, these two tools were applied to the research sample, which was (380) male and female students in the first and second intermediate classes. The research concluded that there is a relationship between e-learning and academic passion among students.
Breast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep
... Show MoreIn this article, Convolution Neural Network (CNN) is used to detect damage and no damage images form satellite imagery using different classifiers. These classifiers are well-known models that are used with CNN to detect and classify images using a specific dataset. The dataset used belongs to the Huston hurricane that caused several damages in the nearby areas. In addition, a transfer learning property is used to store the knowledge (weights) and reuse it in the next task. Moreover, each applied classifier is used to detect the images from the dataset after it is split into training, testing and validation. Keras library is used to apply the CNN algorithm with each selected classifier to detect the images. Furthermore, the performa
... Show MoreDeep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to
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