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A Comprehensive Pressure Distribution Model for Horizontal Well in Bottom-Water Reservoir
Full text linkThe growing application of horizontal well technology provided far-reaching solutions to more realistic phenomena in well test analyses. However, existing models restrict the types of flow regimes by assuming that the dynamics of fluid are controlled by the geometry of the reservoir only. Such an assumption limits the number of flow regimes and hence the accuracy of well test analyses. In this article, all potential flow regimes of a horizontal well in a reservoir supported by bottom water were considered. The conceptual model assumed that the dynamics of the reservoir fluid are a function of the petrophysical properties of the reservoir, the properties of the fluid, and the geometry of the reservoir system. The physical model and the mathematical model were developed based on the conceptual model. The mathematical model is the pressure distribution of the horizontal well in the reservoir. The pressure distribution is in the form of dimensionless pressure and dimensionless pressure derivative functions of reservoir system properties, fluid properties, reservoir system geometry, and dimensionless time. Results of the study show a series of flow patterns along the principal axes or along combinations of the principal axes. Each flow regime could be distinguished by one of the flow patterns and the axes of orientation of the pattern. Each flow regime could be recognized by its characteristic signature in the log-log graph plots of the pressure distribution
Improving Contingency Evaluation In Nigerian 330kv Transmission Grid Using Intelligent Based SSVC
Full text linkThe consistent power failure in Nigerian 330 KV transmission network that had crippled business activities was overcame by introducing improving contingency evaluation in Nigerian 330kv transmission grid using intelligent based SSVC. contingency challenges in Nigerian 330kV transmission grid was characterized and established, conventional SIMULINK model Nigerian 330kV transmission grid was designed, SSVC rule base that will minimize the causes of contingency challenges in Nigerian 330kV transmission grid was developed and ANN was trained in the developed SSVC rule base for immediate minimization of the causes of contingency challenges in Nigerian 330kV transmission grid. Then an algorithm that would implement the process was developed and SIMULINK model for improving contingency evaluation in Nigerian 330KV transmission grid using intelligent based SSVC was designed and results obtained were validated and justified. The results obtained were the conventional Transformer Failure Rate that causes contingency challenges in Nigerian 330kV transmission grid was22%. On the other hand, when an intelligent based SSVC was imbibed into the system, it concurrently reduced it to19.8 %. Finally, with these results obtained, it definitely showed that the percentage improvement in contingency evaluation in Nigerian 330KV transmission grid when an intelligent based SSVC was integrated in the system was2.2%. To characterize and establish the causes of contingency challenges in Nigerian 330kV transmission grid. To design conventional SIMULINK model Nigerian 330kV transmission grid. To develop an SSVC rule base that will minimize the causes of contingency challenges in Nigerian 330kV transmission grid. To train ANN in the developed SSVC rule base for immediate minimization of the causes of contingency challenges in Nigerian 330kV transmission grid. To develop an algorithm that will implement the process. To design a SIMULINK model for Improving contingency evaluation in Nigerian 330KV transmission grid using intelligent based SSVC. To validate and justify percentage improvement in the reduction of causes of contingency challenges in Nigerian 330kV transmission grid with and without an intelligent based SSV
Digital Learning, Digital Economy and Digital Money in Nigeria: The Emerging Criminology of Nexus
Full text linkThe emerging criminological nexus across the digitalisation of learning, money and economy has generated mix reactions across development lines. While some clime examples developed world see it totally as a way to go, some developing countries see it as a threat to their culture and subsistent economy. Little wonder the concept of digital learning via Open distance education aimed at taking learning to the door step of all learners are still suffering despise despite the flexible accessible lifelong promise it holds for all who seek knowledge without discrimination. Rather than embrace it as a connector that anchor the seamless digital money and economy, in some clime crimes of various shades have emerged to subvert the entire essence of that drives knowledge economy. These drawbacks have not taken away the fact that digitalisation has come to stay. The list anyone can do is to embrace its capability to navigate cashless society, digital economy and quality of life. Looking ahead, the landscape of digital skills is expected to evolve continuously. Emerging technologies like artificial intelligence and blockchain will reshape the skills needed. The emphasis on continuous learning and adaptation becomes paramount in this ever-changing environment. Essentially, the narrative of the Nigerian digital economy is incomplete without acknowledging the pivotal role of digital skills as product of ODL. They are not merely tools for employment but catalysts for innovation, empowerment, and national progress. Embracing digital learning is not just an option but a prerequisite for a thriving cashless future and a crucial step towards creating a digitally skilled population out of open and distance learning education
Job Insecurity, Work Life Balance And Quality Of Work Life As Predictors Of Psychological Wellbeing Among Secondary School Teachers In Ibadan South West Local Government, Oyo State.
Full text linkThis paper examines the influence of work-life balance, quality of work life, and job insecurity on psychological wellbeing among secondary school teachers in Ibadan, Oyo State. There were 200 respondents used in the study, about 11 hypotheses were tested. Correlation analysis revealed that work-life balance had no significant relationship with psychological wellbeing (r = -0.03, p > .05) and most of its subcomponents, except for environmental mastery and autonomy, which showed significant negative relationships (r = -0.16, p < .05). This indicates that teachers with higher work-life balance reported lower levels of environmental mastery and autonomy. Quality of work life, however, showed significant positive correlations with psychological wellbeing (r = 0.23, p < .01) and five of its subcomponents, including self-acceptance, positive relations, environmental mastery, purpose in life, and autonomy. Job insecurity also showed positive correlations with psychological wellbeing and its components, but not with personal growth. Independent t-tests were used to test four hypotheses. There was no significant difference in psychological wellbeing between teachers with high and low job insecurity [t(198) = 0.76, p > .05]. However, a significant difference was found based on work-life balance [t(198) = 2.09, p < .05], but in an unexpected direction: teachers with low work-life balance reported higher wellbeing. No significant difference in psychological wellbeing was observed based on quality of work life or gender. Multiple regression analysis showed that work-life balance, quality of work life, and job insecurity jointly predicted psychological wellbeing [R² = 0.07, F(3,196) = 4.77, p < .01], though none of the predictors had a significant independent effect. These predictors also jointly predicted self-acceptance and positive relations with others, with quality of work life and job insecurity emerging as significant individual predictors for each outcome respectively. Overall, the findings suggest that while work-life balance, job insecurity, and quality of work life have some influence on psychological wellbeing, their effects vary across specific dimensions, with quality of work life showing the most consistent positive influence. The results were discussed accordingly
Experimental Study And Analysis Of The Internal Combustion Engine Repair Performance And Sustainability, Using Artificial Neural Network Approach (a Case Study Of Caritas University)
Full text linkThe Caritas University Amorji Nike Internal Combustion Engine testbed system has not functionied in the past five years.The rehabilitation of the Internal Combustion Engine is for optimal performance of the Engine for laboratory determination of both speed,brake power and torque values.The Purpose of rehabilitation and Optimization of Engine performance is to maximize the energy extracted from the fuel by ensuring complete and efficient combustion.The importance of this project is to ensure efficient combustion and reduced fuel consumption.This paper established; optimal air fuel ratio (AFR), the Engine performance and reduced emissions by adopting the Artificial Neural Network approach, for complete analysis of the rehabilitation process.The rehabilitation process involved the servicing of the combustion chamber, the cooling radiator installation and extension of the exhaust system.The analysis of the work carried out, using the Artificial Neural Network ensured the optimal performance of the Internal Combustion Engine.Internal combustion engines are a crucial component of modern transportation systems, but their repair and maintenance pose significant technical and environmental challenges. This research focuses on developing optimized repair techniques for internal combustion engine to improve their performance, reduce emissions, and enhance sustainability. A comprehensive analysis of existing repair methods is conducted, identifying key areas for improvement. Novel repair strategies are then proposed, incorporating advanced materials, coatings, and machining techniques. Experimental validation of the optimized repair techniques demonstrates significant improvements in engine efficiency, power output, and emissions reduction. The results of this research contribute to the development of more sustainable and environmentally friendly internal combustion engine repair practices, supporting the transition towards a more circular and low-carbon transportation sector
Standardized Framework For Assessing The Impact Of Employee Training On Performance In Public Organizations In Nigeria: a Pragmatic Proposal
Full text linkThe study examined a standardized framework for assessing the impact of employee training on performance in public organizations in Nigeria. In Nigeria, the importance of having a standardized framework for assessing the impact of employee training on performance in public organizations in Nigeria cannot be overemphasized. If performance in public organizations is below expectation after the training and development of employees of the organizations, then the existing training and development initiatives and programmes remain effective and efficient in promoting and sustaining organizational performance. The objectives of the study include - to evaluate the long-term impacts of various employee training types on public organizational performance in Nigeria, to collect and analyze employee feedback on past training programs to identify strengths and weaknesses from their perspectives, and to propose a standardized framework for assessing the impact of employee training on performance in the public organizations. The study adopted the Human Capital Theory, and the qualitative research design; relied heavily on secondary source of data, and analyzed the collected data via content method of data analysis. The findings of the study revealed that the long-term impacts of the training types (on-the-job training, off-the-job training, e-learning, mentorship programs) on organizational performance are constrained by funding constraints, lack of quality and relevance training initiatives and programs offered that do not meet the actual needs of employees or organizations; lack of robust systems for monitoring and evaluating the impact of training on performance. Also, that the methods employed to collect feedback from employees regarding training programs include - surveys and questionnaires, focus groups, interviews, and observations; and the proposed framework consists of five key components: training needs assessment, training implementation, immediate evaluation, long-term evaluation, and continuous Improvement. Based on this, the study recommended, among others, that the Federal Government and relevant agencies such as the Office of the Head of Civil Service of the Federation should establish policies that mandate standardized training assessments across all ministries, departments, and agencies (MDAs).
 
Sensitivity of Crossflow to Parametric Study of Complete Pressure Distribution Model for Horizontal Well in a Two-Layered Bounded Extended Reservoir
Full text linkA crossflow interface acts as a constant pressure external boundary. It provides recharge of energy within a layer by fluid influx from another layer. The extent of recharge is determined by the degree of crossflow. Since there is no direct way to determine the degree of crossflow at the scale of a reservoir, parameters that control the behavior of crossflow were used to study its effect on pressure responses. This article is aimed at determining the sensitivity of crossflow to changes in the values of the parameters that control its performance in a two-layered bounded reservoir. Conceptual, physical, and mathematical models were sequentially developed for a horizontal well in a two-layered bounded reservoir with a crossflow interface. A mathematical model for the crossflow interface was derived as a function of fluid properties, reservoir properties, and real time. Quantifying parameters were defined as degree of crossflow, D, and ease of crossflow, E. Various configurations of the two-layered reservoir, resulting in eighteen sets of data, were used to study behaviour of Crossflow. From the results obtained, the degree of crossflow increases as the dimensionless pressure reduces. As ease of crossflow increases, so also does the rate of decline in pressure derivative. Degree of crossflow varies directly as dimensionless well standoff, dimensionless well radius, and dimensionless well length. The degree of crossflow varies inversely as the time normalization factor, dimensionless reservoir width, and dimensionless reservoir length. However, the degree of crossflow is not affected by reservoir thickness and interlayer mobility ratio. Ease of crossflow varies directly as interlayer mobility ratio, dimensionless well length, and dimensionless well radius but inversely as dimensionless well standoff, dimensionless reservoir length, and dimensionless reservoir width. But ease of crossflow is not affected by reservoir thickness. It was observed that optimum oil production and effective reservoir management can be achieved if both layers are produced from the layer with higher mobility. It is therefore recommendable as the best completion strategy for a layered reservoir with a crossflow interface to produce both layers from the layer with higher mobility
Assessment of Diethylene Glycol (Deg) Dehydration System in a Natural Gas Processing System
Full text linkThe natural gas found in Nigeria\u27s Obagi field, specifically in OML 58 where the Obite gas processing plant is located, typically contains water vapour. It is generally assumed that about 98% of gas discoveries in this area are saturated with water. The presence of water in either liquid or vapour form creates technical challenges. This problem is prevented through dehydration to prevent hydrate formation. To achieve optimal production, cost-effectiveness, and improved marginal gains in gas processing, dehydration systems need to be carefully evaluated. This paper offers the use of a simulation tool to tackle the natural gas dehydration system at the Obite Gas Plant. Process conditions of 84bar and 35oC and gas flow rate of 8MMSCFD, as the input data. Results indicate a DEG flow rate of 12.735m3/h, the water volume was reduced to 2.3915lb/MMSCF from an early value of 9.92lb/MMSCF. This is below the pipeline specification. The volume of methane recovered with a flow rate of 74%, for a DEG flow rate of 2.4m3/h, 4.6lb/MMSCF of water recovered in the gas stream. DEG dehydration can be used for dehydration systems due to its ability to meet low temperature and dew point specifications, and low initial and operating costs. After investigating various dehydration units at Obite gas processing facility, it is apparent that DEG can be used alongside TEG and many of the problems encountered and costs incurred could have been prevented with a better engineering understanding of the dehydration system
Assessment of Oil and Gas Waste Water Treatment Technologies. A Review
Full text linkThe rapid growth of the oil and gas industry has led to an increase in the production of wastewater containing contaminants such as hydrocarbons, heavy metals, and salts. These contaminants pose significant environmental and health risks if not properly treated. Therefore, various technologies have been developed to treat oil and gas wastewater. This review article aims to assess the various treatment technologies available and their efficiency in treating these wastewater. The technologies reviewed include physical, chemical, and biological treatments. Physical methods including flocculation, sedimentation, and filtration techniques are effective in removing suspended solids. Chemical methods, such as coagulation and advanced oxidation processes, are effective in removing hydrocarbons and heavy metals. Biological treatments, including microbial fuel cells and constructed wetlands, have also shown promising results in treating oil and gas wastewater. The review found that a combination of two or more of these technologies can provide efficient and cost-effective treatment of oil and gas wastewater. However, further research is needed to determine the best treatment approach for various types of oil and gas wastewater
Improving Constant Power Supply By Integrating Solar To The Microgrid Using Intelligent Based Ultracapacitor
Full text linkThe increasing demand for reliable and sustainable power supply has led to the integration of renewable energy sources, particularly solar energy, into micro grids. However, the intermittent and variable nature of solar generation poses significant challenges to maintaining a constant power supply. This study proposes an intelligent-based ultra-capacitor system to enhance the performance and stability of solar-integrated micro grids. By employing intelligent control algorithms, such as Artificial Neural Networks (ANN) or Fuzzy Logic Controllers (FLC), the ultra-capacitor is optimized to manage energy storage and delivery efficiently. The intelligent controller dynamically responds to fluctuations in solar output and load demand, ensuring seamless energy balancing, voltage stability, and reduced response time. Simulation and modeling results demonstrate that the integration of intelligent ultra-capacitors significantly improves the reliability, power quality, and continuity of supply within the micro grid. This approach offers a viable solution for addressing the limitations of conventional energy storage systems, paving the way for smarter and more resilient distributed energy networks. The conventional Solar irradiance variability that causes power failure in integration of solar to the micro grid was 43%. On the other hand, when an intelligent based ultra-capacitor was integrated into the system, it instantly reduced it to37.2% and the conventional Faults in distribution lines that causes power failure in integration of solar to the micro grid was9%. Meanwhile, when an intelligent based ultra-capacitor was inculcated into the system, it simultaneously reduced to7.8%. Finally, with these results obtained, the percentage improvement in constant power supply by integrating solar to the micro grid when an intelligent based ultra-capacitor was integrated into the system was 1.2%