Wellbore instability is one of the major issues observed throughout the drilling operation. Various wellbore instability issues may occur during drilling operations, including tight holes, borehole collapse, stuck pipe, and shale caving. Rock failure criteria are important in geomechanical analysis since they predict shear and tensile failures. A suitable failure criterion must match the rock failure, which a caliper log can detect to estimate the optimal mud weight. Lack of data makes certain wells' caliper logs unavailable. This makes it difficult to validate the performance of each failure criterion. This paper proposes an approach for predicting the breakout zones in the Nasiriyah oil field using an artificial neural network. It also presents the optimal mud weight window for this field, which can be used to optimise the mud weights to minimise the wellbore instability issues. The results showed that an artificial neural network is a powerful tool for determining the breakout zones using the input data. The obtaining root mean square error and the determination coefficient were respectively 0.0082 and 0.959, by which the 1D MEM gave a high match between the predicted wellbore instabilities using the Mogi-failure criterion and the predicted breakout using the ANN model. Most borehole enlargements occur due to formation shear failures because of using low mud weights during drilling. The conclusion clarify the1.35 g/cc is the optimal mud weights for drilling new wells in this field of interest with fewer drilling issues.
Crime is a threat to any nation’s security administration and jurisdiction. Therefore, crime analysis becomes increasingly important because it assigns the time and place based on the collected spatial and temporal data. However, old techniques, such as paperwork, investigative judges, and statistical analysis, are not efficient enough to predict the accurate time and location where the crime had taken place. But when machine learning and data mining methods were deployed in crime analysis, crime analysis and predication accuracy increased dramatically. In this study, various types of criminal analysis and prediction using several machine learning and data mining techniques, based o
The Electrical power system has become vast and more complex, so it is subjected to sudden changes in load levels. Stability is an important concept which determines the stable operation of the power system. Transient stability analysis has become one of the significant studies in the power system to ensure the system stability to withstand a considerable disturbance. The effect of temporary occurrence can lead to malfunction of electronic control equipment. The application of flexible AC transmission systems (FACTS) devices in the transmission system have introduced several changes in the power system. These changes have a significant impact on the power system protection, due to differences inline impedance, line curre
... Show MoreAbstract Objectives: This research seeks to highlight one of the important topics artificial intelligence and its impact on education and media. This issue has received considerable attention from international institutions and organizations in order to keep pace with the world's current progress. The study provided an overview of the concept of artificial intelligence, its definitions, its importance and characteristics and its impact on education in general and on the student and teacher in particular, as well as linking the subject of education to the media because social media that is one of the media has a great impact on the academic community. Methods: This study relied on the analytical descriptive curriculum where one of the curr
... Show MoreFor the duration of the last few many years many improvement in computer technology, software program programming and application production had been followed with the aid of diverse engineering disciplines. Those trends are on the whole focusing on synthetic intelligence strategies. Therefore, a number of definitions are supplied, which recognition at the concept of artificial intelligence from exclusive viewpoints. This paper shows current applications of artificial intelligence (AI) that facilitate cost management in civil engineering tasks. An evaluation of the artificial intelligence in its precise partial branches is supplied. These branches or strategies contributed to the creation of a sizable group of fashions s
... Show MoreThe use of artificial intelligence (AI) technology is rapidly expanding in nursing and society. However, its use in healthcare comes with a number of challenges and concerns. The authors of this article use the sociotechnical model to consider the expanding use of AI in nursing and healthcare from a global perspective. Select references from the literature are used to support this important discussion for nurses and other healthcare professionals. Artificial intelligence is a major innovation that, if used properly, can reduce errors and improve efficiency and healthcare quality. It has also been shown to increase patient support, healthcare access and patient care. Here the authors address some of the limitations and challenges of
... Show MoreEconomic units can benefit from the cleaner production strategy, which aims to reduce the environmental impact of economic activities while improving efficiency and profitability. Accordingly, the aim of the research was to clarify the knowledge foundations of cleaner production costs and to indicate their role in reducing the costs of poor quality (the costs of failure). A set of conclusions has been reached, the most important of which is that cleaner production has achieved a reduction in the costs of external failure, represented by the costs of guarantee, by an amount of 12,339,000 dinars. Contributes to reducing the costs of failure, and based on the conclusions, a set of recommendations were presented, the most important of w
... Show MoreThe aim of this paper is to approximate multidimensional functions by using the type of Feedforward neural networks (FFNNs) which is called Greedy radial basis function neural networks (GRBFNNs). Also, we introduce a modification to the greedy algorithm which is used to train the greedy radial basis function neural networks. An error bound are introduced in Sobolev space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result is published in [16]).
The objective of the study was to predict crop coefficient (K) values for cucumber inside the greenhouse during the growing season 2014, using watermarks gypsum blocks and atmometer c apparatus during the growing stages and to compare the predicted values of the crop coefficient with different methods and approaches. The study was conducted in the greenhouses field within Al-Mahawil Township, 70 km south of Baghdad, Iraq. The watermarks soil water sensors and atmometer apparatus were used to measure crop evapotranspiration and reference evapotranspiration on daily basis, respectively. The comparison and the statistical analysis between the calculated K in this study and values obtained from greenhouse gave a good agreement. The root mean
... Show MoreThe zeolite's textural properties have a significant effect on zeolite's effectiveness in the different industrial processes. This research aimed to study the textual properties of the NaX and FeX zeolites using the nitrogen adsorption-desorption technique at a constant low temperature. According to the International Union of Pure and Applied Chemistry, the adsorption-desorption isotherm showed that the studied materials were mixed kinds I/II isotherms and H3 type hysteresis. The Brunauer-Emmett-Teller isotherm was the best model to describe the nitrogen adsorption-desorption better than the Langmuir and Freundlich isotherms. The obtained adsorption capacity and Brunauer-Emmett-Teller surface area values for NaX were greater than FeX. Ac
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