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Simulate reservoirs effectively to extract the maximum oil, gas and profit, with this book and free simlation software on companion web site.
Fundamentals of Applied Reservoir Engineering introduces early career reservoir engineers and those in other oil and gas disciplines to the fundamentals of reservoir engineering. Given that modern reservoir engineering is largely centered on numerical computer simulation and that reservoir engineers in the industry will likely spend much of their professional career building and running such simulators, the book aims to encourage the use of simulated models in an appropriate way and exercising good engineering judgment to start the process for any field by using all available methods, both modern simulators and simple numerical models, to gain an understanding of the basic 'dynamics' of the reservoir –namely what are the major factors that will determine its performance. With the valuable addition of questions and exercises, including online spreadsheets to utilize day-to-day application and bring together the basics of reservoir engineering, coupled with petroleum economics and appraisal and development optimization, Fundamentals of Applied Reservoir Engineering will be an invaluable reference to the industry professional who wishes to understand how reservoirs fundamentally work and to how a reservoir engineer starts the performance process. - Covers reservoir appraisal, economics, development planning, and optimization to assist reservoir engineers in their decision-making. - Provides appendices on enhanced oil recovery, gas well testing, basic fluid thermodynamics, and mathematical operators to enhance comprehension of the book's main topics. - Offers online spreadsheets covering well test analysis, material balance, field aggregation and economic indicators to help today's engineer apply reservoir concepts to practical field data applications. - Includes coverage on unconventional resources and heavy oil making it relevant for today's worldwide reservoir activity.
Presents numerical methods for reservoir simulation, with efficient implementation and examples using widely-used online open-source code, for researchers, professionals and advanced students. This title is also available as Open Access on Cambridge Core.
The volume provides clear and concise information on reservoir engineering methods, ranging from specific geological and geophysical techniques applied to reservoirs, to the basics of reservoir simulation, with reference to well logging, fluid PVT studies and well testing. Emphasis is placed on recent methods such as the use of type curves in well test interpretation, and on horizontal drain holes. The information will help all specialists in the relevant disciplines such as geologists, geophysicists, production engineers and drillers. It will also be useful to a broader range of specialists such as computer scientists, legal experts, economists and research workers, in placing their work within a wider professional context and incorporating it into a multidisciplinary field of activity.
This book describes the state of the art of the mathematical theory and numerical analysis of imaging. Some of the applications covered in the book include computerized tomography, magnetic resonance imaging, emission tomography, electron microscopy, ultrasound transmission tomography, industrial tomography, seismic tomography, impedance tomography, and NIR imaging.
Reservoir simulation has been in practice for more than 50 years, but it has recently gained significant momentum because of its wider application to the increasingly complex reservoir systems of today. Reservoir Simulation: Problems and Solutions provides petroleum engineers with extensive practice in the art of problem solving, strengthening their critical-thinking solution strategies and preparing them for the unique problems they will encounter in this dynamic field. Built on the fundamental concepts and solutions of the original exercises found in Basic Applied Reservoir Simulation (Turgay Ertekin, Jamal H. Abou-Kassem, and Gregory R. King), this new book provides an additional 180 exercises and solutions that fully illustrate the intricacies of reservoir-simulation methodology. Turgay Ertekin is Professor Emeritus of Petroleum and Natural Gas Engineering at the Pennsylvania State University, where he has been a member of the faculty for more than 40 years. Qian Sun is a research engineer at New Mexico Institute of Mining and Technology. His research focuses mainly on numerical reservoir simulation and artificial-intelligence applications in reservoir Engineering. Jian Zhang is a PhD graduate at Penn State. His research focuses on rate- and pressure-transient analysis, numerical reservoir simulation, artificial neural networks and neuro-simulation.
Petroleum Reservoir Simulation, Second Edition, introduces this novel engineering approach for petroleum reservoir modeling and operations simulations. Updated with new exercises, a new glossary and a new chapter on how to create the data to run a simulation, this comprehensive reference presents step-by-step numerical procedures in an easy to understand format. Packed with practical examples and guidelines, this updated edition continues to deliver an essential tool for all petroleum and reservoir engineers. Includes new exercises, a glossary and references Bridges research and practice with guidelines on introducing basic reservoir simulation parameters, such as history matching and decision tree content Helps readers apply knowledge with assistance on how to prepare data files to run a reservoir simulator
Reservoir Engineering focuses on the fundamental concepts related to the development of conventional and unconventional reservoirs and how these concepts are applied in the oil and gas industry to meet both economic and technical challenges. Written in easy to understand language, the book provides valuable information regarding present-day tools, techniques, and technologies and explains best practices on reservoir management and recovery approaches. Various reservoir workflow diagrams presented in the book provide a clear direction to meet the challenges of the profession. As most reservoir engineering decisions are based on reservoir simulation, a chapter is devoted to introduce the topic in lucid fashion. The addition of practical field case studies make Reservoir Engineering a valuable resource for reservoir engineers and other professionals in helping them implement a comprehensive plan to produce oil and gas based on reservoir modeling and economic analysis, execute a development plan, conduct reservoir surveillance on a continuous basis, evaluate reservoir performance, and apply corrective actions as necessary. - Connects key reservoir fundamentals to modern engineering applications - Bridges the conventional methods to the unconventional, showing the differences between the two processes - Offers field case studies and workflow diagrams to help the reservoir professional and student develop and sharpen management skills for both conventional and unconventional reservoirs
Reservoir Simulation: Machine Learning and Modeling helps the engineer step into the current and most popular advances in reservoir simulation, learning from current experiments and speeding up potential collaboration opportunities in research and technology. This reference explains common terminology, concepts, and equations through multiple figures and rigorous derivations, better preparing the engineer for the next step forward in a modeling project and avoid repeating existing progress. Well-designed exercises, case studies and numerical examples give the engineer a faster start on advancing their own cases. Both computational methods and engineering cases are explained, bridging the opportunities between computational science and petroleum engineering. This book delivers a critical reference for today's petroleum and reservoir engineer to optimize more complex developments. - Understand commonly used and recent progress on definitions, models, and solution methods used in reservoir simulation - World leading modeling and algorithms to study flow and transport behaviors in reservoirs, as well as the application of machine learning - Gain practical knowledge with hand-on trainings on modeling and simulation through well designed case studies and numerical examples.