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Since the turn of the century, geology has advanced dramatically, with materials derived from extra-terrestrial sources meaning that it now encompasses cosmology, and new technologies providing ever more sophisticated possibilities for the conducting of research. This book, Unconventional Methods for Geoscience, Shale Gas and Petroleum in the 21st Century, aims to provide research directions for geology in the 21st century. As Eric Hobsbawm wrote, it is difficult to write the history of one’s own days, and selecting influential methods was no easy task, but an attempt has been made to include the most influential papers that represent the smart geology of the first few decades of the 21st ...
This book presents the proceedings of the 4th International Conference on Integrated Petroleum Engineering and Geosciences 2016 (ICIPEG 2016), held under the banner of World Engineering, Science & Technology Congress (ESTCON 2016) at Kuala Lumpur Convention Centre from August 15 to 17, 2016. It presents peer-reviewed research articles on exploration, while also exploring a new area: shale research. In this time of low oil prices, it highlights findings to maintain the exchange of knowledge between researchers, serving as a vital bridge-builder between engineers, geoscientists, academics, and industry.
This book presents the proceedings of the 3rd International Conference on Integrated Petroleum Engineering and Geosciences 2014 (ICIPEG2014). Topics covered on the petroleum engineering side include reservoir modeling and simulation, enhanced oil recovery, unconventional oil and gas reservoirs, production and operation. Similarly geoscience presentations cover diverse areas in geology, geophysics palaeontology and geochemistry. The selected papers focus on current interests in petroleum engineering and geoscience. This book will be a bridge between engineers, geoscientists, academicians and industry.
Many approaches have sprouted from artificial intelligence (AI) and produced major breakthroughs in the computer science and engineering industries. Deep learning is a method that is transforming the world of data and analytics. Optimization of this new approach is still unclear, however, and there’s a need for research on the various applications and techniques of deep learning in the field of computing. Deep Learning Techniques and Optimization Strategies in Big Data Analytics is a collection of innovative research on the methods and applications of deep learning strategies in the fields of computer science and information systems. While highlighting topics including data integration, computational modeling, and scheduling systems, this book is ideally designed for engineers, IT specialists, data analysts, data scientists, engineers, researchers, academicians, and students seeking current research on deep learning methods and its application in the digital industry.
This conference proceeding gather a selection of peer-reviewed papers presented at the 1st International Conference on Artificial Intelligence for Smart Community (AISC 2020), held as a virtual conference on 17–18 December 2020, with the theme Re-imagining Artificial Intelligence (AI) for Smart Community to apply computational intelligence for biomedical instruments, automation & control, and smart community to develop suitable solution for various real-world application. The conference virtually brought together researchers, scientists, engineers, industrial professionals, and students presenting important results in the related field of healthcare technology, soft computing technologies, IoT, evolutionary computations, automation and control, smart manufacturing and smart cities. Researchers and scientist working in the allied domain of Artificial Intelligence and others will find the book useful as it will contain some latest computational intelligence methodologies and applications.
This book presents articles from the International Conference on Improved Oil Recovery, CIOR 2017, held in Bandung, Indonesia. Highlighting novel technologies in the area of Improved Oil Recovery, it discusses a range of topics, including enhanced oil recovery, hydraulic fracturing, production optimization, petrophysics and formation evaluation.
Get started with MATLAB for deep learning and AI with this in-depth primer. In this book, you start with machine learning fundamentals, then move on to neural networks, deep learning, and then convolutional neural networks. In a blend of fundamentals and applications, MATLAB Deep Learning employs MATLAB as the underlying programming language and tool for the examples and case studies in this book. With this book, you'll be able to tackle some of today's real world big data, smart bots, and other complex data problems. You’ll see how deep learning is a complex and more intelligent aspect of machine learning for modern smart data analysis and usage. What You'll Learn Use MATLAB for deep learning Discover neural networks and multi-layer neural networks Work with convolution and pooling layers Build a MNIST example with these layers Who This Book Is For Those who want to learn deep learning using MATLAB. Some MATLAB experience may be useful.
This book presents the proceedings of the 3rd International Conference on Integrated Petroleum Engineering and Geosciences 2014 (ICIPEG2014). Topics covered on the petroleum engineering side include reservoir modeling and simulation, enhanced oil recovery, unconventional oil and gas reservoirs, production and operation. Similarly geoscience presentations cover diverse areas in geology, geophysics palaeontology and geochemistry. The selected papers focus on current interests in petroleum engineering and geoscience. This book will be a bridge between engineers, geoscientists, academicians and industry.
This book describes the application of modern information technology to reservoir modeling and well management in shale. While covering Shale Analytics, it focuses on reservoir modeling and production management of shale plays, since conventional reservoir and production modeling techniques do not perform well in this environment. Topics covered include tools for analysis, predictive modeling and optimization of production from shale in the presence of massive multi-cluster, multi-stage hydraulic fractures. Given the fact that the physics of storage and fluid flow in shale are not well-understood and well-defined, Shale Analytics avoids making simplifying assumptions and concentrates on facts (Hard Data - Field Measurements) to reach conclusions. Also discussed are important insights into understanding completion practices and re-frac candidate selection and design. The flexibility and power of the technique is demonstrated in numerous real-world situations.
Petrophysical Characterization and Fluids Transport in Unconventional Reservoirs presents a comprehensive look at these new methods and technologies for the petrophysical characterization of unconventional reservoirs, including recent theoretical advances and modeling on fluids transport in unconventional reservoirs. The book is a valuable tool for geoscientists and engineers working in academia and industry. Many novel technologies and approaches, including petrophysics, multi-scale modelling, rock reconstruction and upscaling approaches are discussed, along with the challenge of the development of unconventional reservoirs and the mechanism of multi-phase/multi-scale flow and transport in these structures. - Includes both practical and theoretical research for the characterization of unconventional reservoirs - Covers the basic approaches and mechanisms for enhanced recovery techniques in unconventional reservoirs - Presents the latest research in the fluid transport processes in unconventional reservoirs