Compositional Grading in Oil and Gas Reservoirs offers instruction, examples, and case studies on how to answer the challenges of modeling a compositional gradient subject. Starting with the basics on PVT analysis, applied thermodynamics, and full derivations of irreversible thermodynamic-based equations, this critical reference explains gravity-modified equations to be applied to reservoirs, enabling engineers to obtain fluid composition at any point of the reservoir from measured data to create a stronger model calibration. Once model-parameters are re-estimated, new sensibility can be acquired for more accurate modeling of composition, aiding engineers with stronger production curves, reserve estimations, and design of future development strategies. Multiple examples and case studies are included to show the application of the theory from very simple to more complex systems, such as actual reservoirs influenced by thermal diffusion and gravity simultaneously. Other example include a layer for which asphaltene precipitation takes place in the reservoir and three –phase flash algorithms for liquid-liquid-vapor equilibrium calculations, detailing the techniques necessary to ensure convergence. The book combines practical studies with the importance in modeling more complex phenomena, filling a gap for current and upcoming reservoir engineers to expand on solutions and make sense of their reservoir's output results. - Presents a deeper level of detail on the heterogeneity composition and thermo-physical properties of petroleum fluids in the reservoir - Includes tactics on how to Increase reliability of reservoir simulation initialization, with practice examples at the end of each chapter - Helps readers make sense of compositional grading, with coverage on both theory and application that fulfill a gap in research on reservoir simulation
This book is an introduction to the use of machine learning and data-driven approaches in fluid simulation and animation, as an alternative to traditional modeling techniques based on partial differential equations and numerical methods – and at a lower computational cost. This work starts with a brief review of computability theory, aimed to convince the reader – more specifically, researchers of more traditional areas of mathematical modeling – about the power of neural computing in fluid animations. In these initial chapters, fluid modeling through Navier-Stokes equations and numerical methods are also discussed. The following chapters explore the advantages of the neural networks approach and show the building blocks of neural networks for fluid simulation. They cover aspects related to training data, data augmentation, and testing. The volume completes with two case studies, one involving Lagrangian simulation of fluids using convolutional neural networks and the other using Generative Adversarial Networks (GANs) approaches.
This book provides a state-of-the-art review of the fail-safe and damage tolerance approaches, allowing weight savings and increasing aircraft reliability and structural integrity. The application of the damage tolerance approach requires extensive know-how of the fatigue and fracture properties, corrosion strength, potential failure modes and non-destructive inspection techniques, particularly minimum detectable defect and inspection intervals. In parallel, engineering practice involving damage tolerance requires numerical techniques for stress analysis of cracked structures. These evolved from basic mode I evaluations using rough finite element approaches, to current 3D modeling based on energetic approaches as the VCCT, or simulation of joining processes. This book provides a concise introduction to this subject.
Artificial Intelligence (AI) has the potential to reshape the global economy, especially in the realm of labor markets. Advanced economies will experience the benefits and pitfalls of AI sooner than emerging market and developing economies, largely due to their employment structure focused on cognitive-intensive roles. There are some consistent patterns concerning AI exposure, with women and college-educated individuals more exposed but also better poised to reap AI benefits, and older workers potentially less able to adapt to the new technology. Labor income inequality may increase if the complementarity between AI and high-income workers is strong, while capital returns will increase wealth inequality. However, if productivity gains are sufficiently large, income levels could surge for most workers. In this evolving landscape, advanced economies and more developed emerging markets need to focus on upgrading regulatory frameworks and supporting labor reallocation, while safeguarding those adversely affected. Emerging market and developing economies should prioritize developing digital infrastructure and digital skills
In the aftermath of the COVID-19 pandemic, emerging market and developing economies are grappling with economic scarring, social tension, and reduced policy space. Policy actions are already urgently needed to boost growth in the near term and support the ongoing green transition. At the same time, high public debt and persistently high inflation have constrained policy space, posing difficult policy trade-offs. This Staff Discussion Note focuses on emerging market and developing economies and proposes a framework for prioritization, packaging, and sequencing of macrostructural reforms to accelerate growth, alleviate policy trade-offs, and support the green transition. The note shows that prioritizing the removal of the most binding constraints on economic activity, bundling reforms (governance, business deregulation, and external sector reforms), and appropriate sequencing of other reforms (such as labor market and credit sector reforms) can help front-load reform gains. In emerging market and developing economies with large initial structural gaps, the estimated output effects of such a major reform package are sizable—about 4 percent in two years and 8 percent in four years. Achieving higher growth and lower absolute carbon emissions over time requires a well-designed strategy that includes both macrostructural and green reforms.
This book provide a comprehensive coverage of the latest and most relevant knowledge, developments, solutions, and practical applications, related to e-Health, this new field of knowledge able to transform the way we live and deliver services, both from the technological and social perspectives"--Provided by publisher.
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