Reservoir permeability plays a crucial role in characterizing reservoirs and predicting the present and future production of hydrocarbon reservoirs. Data logging is a good tool for assessing the entire oil well section's continuous permeability curve. Nuclear magnetic resonance logging measurements are minimally influenced by lithology and offer significant benefits in interpreting permeability. The Schlumberger-Doll-Research model utilizes nuclear magnetic resonance logging, which accurately estimates permeability values. The approach of this investigation is to apply artificial neural networks and core data to predict permeability in wells without a nuclear magnetic resonance log. The Schlumberger-Doll-Research permeability is used to train the model, where the model prediction result is validated with core permeability. Seven oil well logs were used as input parameters, and the model was constructed with Techlog software. The predicted permeability with the model compared with Schlumberger-Doll-Research permeability as a cross plot, which results in the correlation coefficient of 94%, while the predicted permeability validated with the core permeability of the well, which obtains good agreement where R2 equals 80%. The model was utilized to forecast permeability in a well that did not have a nuclear magnetic resonance log, and the predicted permeability was cross-plotted against core permeability as a validation step, with a correlation coefficient of 77%. As a result, the low percentage of matching was due to data limitations, which demonstrated that as the amount of data used to train the model increased, so did the precision.
In this research, that been focused on the most important economic benefits expected when applying the three standards of sustainability in construction projects (economic, environmental and social). Fuzzy AHP, a multi-decision decision-making technique for evaluating construction projects. Which when used we get the speed and accuracy in the results. Using this technique will reduce uncertainties decisions significantly (fuzzy environment), that found in most projects .The results of the data analysis showed that the economic standards take the greatest relative importance (60%) among the three sustainability standards. Therefore, the implementation of any standards need a cost so the economic benefit of any proje
... Show MoreCluster analysis (clustering) is mainly concerned with dividing a number of data elements into clusters. The paper applies this method to create a gathering of symmetrical government agencies with the aim to classify them and understand how far they are close to each other in terms of administrative and financial corruption by means of five variables representing the prevalent administrative and financial corruption in the state institutions. Cluster analysis has been applied to each of these variables to understand the extent to which these agencies are close to other in each of the cases related to the administrative and financial corruption.
A field study aimed at identifying the reality of the application of strategic management in the colleges of education/ University of Baghdad. The research adopted the descriptive analytical approach. The research community, consisting of 801 faculty teachers, has been identified. The research sample was selected in a simple random way and represented 15% of the research community, totalling 124 teaching members. A questionnaire was constructed that included (46) items divided between areas (strategic objectives, strategy planning and formulation, implementation of the strategy, and evaluation of the strategy). The honesty and consistency of the tool was verified. The researcher analyzed the research data using SPSS. The most important resu
... Show MoreNon-additive measures and corresponding integrals originally have been introduced by Choquet in 1953 (1) and independently defined by Sugeno in 1974 (2) in order to extend the classical measure by replacing the additivity property to non-additive property. An important feature of non –additive measures and fuzzy integrals is that they can represent the importance of individual information sources and interactions among them. There are many applications of non-additive measures and fuzzy integrals such as image processing, multi-criteria decision making, information fusion, classification, and pattern recognition. This paper presents a mathematical model for discussing an application of non-additive measures and corresp
... Show MoreFusarium pseudograminearum and Fusarium graminearum commonly cause crown rot (FCR) and head blight (FHB) in wheat, respectively. Disease infection and spread can be reduced by the deployment of resistant cultivars or through management practices that limit inoculum load. Plants deficient in micronutrients, including zinc, tend to be more susceptible to many diseases. On the other hands, and zinc deficiency in cereals is widespread in Australian soils. Zinc deficiency may have particular relevance to crown rot, the most important and damaging Fusarium disease of wheat and barley in Australia. Four wheat genotypes; Batavia, Sunco and two lines from the International Maize and Wheat Improvement Center (CIMMYT) were tested for response
... Show MoreAutomated detection of Dubas palm infestation by image processing techniques has practical significance as it can improve agricultural efficiency, increase crop yield and quality, protect the environment, and provide data-driven insights. It also reduces the human effort required for pest control and enhances sustainability. In this study, we aimed to automate the detection of Dubas bug infestation in palm trees using deep learning with transfer learning residual neural networks. Based on four models: InceptionResNetV2, ResNet18, ResNet50, and ResNet101, the data used in this study were obtained by drone photography, many images were taken, and then the infected area was extracted. Using two types of data, 185 infected images and 185 health
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Genetic material is the most important component of cells because it contains the genetic information; hence any disruption to the structure chromosome of cells could lead to very bad results. Genotoxicity use to evaluate the safety of any chemical compounds on genetic materials. Artificial food flavoring additive are chemical substances to produce specific placebo effects added to foods but impart specific flavor to it.
The present study evaluates the genotoxic effect of artificial food flavoring additive on structure of chromosomes at three different concentrations (50%, 100%and 150%) on both bone marrow cells and spleen cells in mice for fourteen successive days. It was found that artificial food flavoring addit
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