Fundamentals of Gas Lift Engineering: Well Design and Troubleshooting discusses the important topic of oil and gas reservoirs as they continue to naturally deplete, decline, and mature, and how more oil and gas companies are trying to divert their investments in artificial lift methods to help prolong their assets. While not much physically has changed since the invention of the King Valve in the 1940s, new developments in analytical procedures, computational tools and software, and many related technologies have completely changed the way production engineers and well operators face the daily design and troubleshooting tasks and challenges of gas lift, which can now be carried out faster, and in a more accurate and productive way, assuming the person is properly trained. This book fulfills this training need with updates on the latest gas lift designs, troubleshooting techniques, and real-world field case studies that can be applied to all levels of situations, including offshore. Making operational and troubleshooting techniques central to the discussion, the book empowers the engineer, new and experienced, to analyze the challenge involved and make educated adjustments and conclusions in the most economical and practical way. Packed with information on computer utilization, inflow and outflow performance analysis, and worked calculation examples made for training, the book brings fresh air and innovation to a long-standing essential component in a well's lifecycle. - Covers essential gas lift design, troubleshooting, and the latest developments in R&D - Provides real-world field experience and techniques to solve both onshore and offshore challenges - Offers past and present analytical and operational techniques available in an easy-to-read manner - Features information on computer utilization, inflow and outflow performance analysis, and worked calculation training examples

This volume presents state-of-the-art of reviews in the field of multiphase flow. In focusses on nonlinear aspects of multiphase flow networks as well as visualization experiments. The first chapter presents nonlinear aspects or deterministic chaos issues in the systems of multi-phase reactors. The second chapter reviews two-phase flow dynamics in combination with complex network theory. The third chapter discusses evaporation mechanism in the wick of copper heat pipes. The last chapter investigates numerically the flow dynamics and heat and mass transfer in the laminar and turbulent boundary layer on the flat vertical plate.

Completions are the conduit between hydrocarbon reservoirs and surface facilities. They are a fundamental part of any hydrocarbon field development project. The have to be designed for safely maximising the hydrocarbon recovery from the well and may have to last for many years under ever changing conditions. Issues include: connection with the reservoir rock, avoiding sand production, selecting the correct interval, pumps and other forms of artificial lift, safety and integrity, equipment selection and installation and future well interventions. - Course book based on course well completion design by TRACS International - Unique in its field: Coverage of offshore, subsea, and landbased completions in all of the major hydrocarbon basins of the world - Full colour

This book is useful to flow assurance engineers, students, and industries who wish to be flow assurance authorities in the twenty-first-century oil and gas industry. The use of digital or artificial intelligence methods in flow assurance has increased recently to achieve fast results without any thorough training effectively. Generally, flow assurance covers all risks associated with maintaining the flow of oil and gas during any stage in the petroleum industry. Flow assurance in the oil and gas industry covers the anticipation, limitation, and/or prevention of hydrates, wax, asphaltenes, scale, and corrosion during operation. Flow assurance challenges mostly lead to stoppage of production or plugs, damage to pipelines or production facilities, economic losses, and in severe cases blowouts and loss of human lives. A combination of several chemical and non-chemical techniques is mostly used to prevent flow assurance issues in the industry. However, the use of models to anticipate, limit, and/or prevent flow assurance problems is recommended as the best and most suitable practice. The existing proposed flow assurance models on hydrates, wax, asphaltenes, scale, and corrosion management are challenged with accuracy and precision. They are not also limited by several parametric assumptions. Recently, machine learning methods have gained much attention as best practices for predicting flow assurance issues. Examples of these machine learning models include conventional approaches such as artificial neural network, support vector machine (SVM), least square support vector machine (LSSVM), random forest (RF), and hybrid models. The use of machine learning in flow assurance is growing, and thus, relevant knowledge and guidelines on their application methods and effectiveness are needed for academic, industrial, and research purposes. In this book, the authors focus on the use and abilities of various machine learning methods in flow assurance. Initially, basic definitions and use of machine learning in flow assurance are discussed in a broader scope within the oil and gas industry. The rest of the chapters discuss the use of machine learning in various flow assurance areas such as hydrates, wax, asphaltenes, scale, and corrosion. Also, the use of machine learning in practical field applications is discussed to understand the practical use of machine learning in flow assurance.

Due to the influence of pore-throat size distribution, pore connectivity, and microscale fractures, the transport, distribution, and residual saturation of fluids in porous media are difficult to characterize. Petrophysical methods in natural porous media have attracted great attention in a variety of fields, especially in the oil and gas industry. A wide range of research studies have been conducted on the characterization of porous media covers and multiphase flow therein. Reliable approaches for characterizing microstructure and multiphase flow in porous media are crucial in many fields, including the characterization of residual water or oil in hydrocarbon reservoirs and the long-term storage of supercritical CO2 in geological formations. This book gathers together 15 recent works to emphasize fundamental innovations in the field and novel applications of petrophysics in unconventional reservoirs, including experimental studies, numerical modeling (fractal approach), and multiphase flow modeling/simulations. The relevant stakeholders of this book are authorities and service companies working in the petroleum, subsurface water resources, air and water pollution, environmental, and biomaterial sectors.

The book is intended for practicing engineers in the oil industry, researchers, and graduate students interested in designing and simulating offshore hydrocarbon production systems. It approaches offshore oil production systems from an integrated perspective that combines the modeling of thermophysical properties of reservoir fluids and their flow as a multiphase mixture in wellbores, flow lines, and risers. The first part of the book presents an internally consistent method to compute the critical parameters and acentric factor of Single Carbon Number (SCN) fractions of petroleum mixtures using state-of-the-art multivariate fitting techniques. The procedure is illustrated and validated using flash and differential liberation data from actual field samples. In the second part of the book, mechanistic multiphase flow models are discussed in light of their ability to predict the pressure, temperature, and phase holdup of production fluids in wellbores, flow lines, and risers. Multivariate fitting procedures are again applied to evaluate the sensitivity of the results with respect to closure relationship parameters, such as slug body gas holdup, wall shear stress, and wall roughness in pipelines and production tubing. Finally, the modeling framework is validated using actual field data from offshore production wells.

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