Machine Learning And Flow Assurance In Oil And Gas Production

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.

The precipitation and deposition of solids are a major challenge in the production of oil and gas. Flow assurance solids are formed because of unavoidable changes in temperature, pressure and composition of the oil-gas-water flowstream, from reservoir conditions to processing conditions. The advent of subsea production and the increased exploitation of heavy crudes have made flow assurance issues dominant in ensuring efficient and safe exploitation of hydrocarbon assets. Five troublesome flow assurance solids are described in the book: asphaltene, paraffin wax, natural gas hydrate, naphthenate and inorganic scale. These big-five solids are presented in stand-alone chapters. Each chapter is designed to be readable without clutter. Derivations of equations and descriptions of supporting details are given in several appendices. The book is intended for professional engineers and natural scientist working in E&P companies, engineering companies, service companies and specialized companies. An understanding of the big-five solids is required throughout the lifetime of oil and gas assets, from early development to abandonment. The technical, safety and environmental risks associated with deposition problems in near-wellbore formations, production tubing, wellhead equipment, flowlines and processing facilities, are relevant for decisions in the oil and gas industry and in outside regulatory and financial entities.

The precipitation and deposition of solids are a major challenge in the production of oil and gas. Flow assurance solids are formed because of unavoidable changes in temperature, pressure and composition of the oil-gas-water flowstream, from reservoir conditions to processing conditions. The advent of subsea production and the increased exploitation of heavy crudes have made flow assurance issues dominant in ensuring efficient and safe exploitation of hydrocarbon assets. Five troublesome flow assurance solids are described in the book: asphaltene, paraffin wax, natural gas hydrate, naphthenate and inorganic scale. These big-five solids are presented in stand-alone chapters. Each chapter is designed to be readable without clutter. Derivations of equations and descriptions of supporting details are given in several appendices. The book is intended for professional engineers and natural scientist working in E&P companies, engineering companies, service companies and specialized companies. An understanding of the big-five solids is required throughout the lifetime of oil and gas assets, from early development to abandonment. The technical, safety and environmental risks associated with deposition problems in near-wellbore formations, production tubing, wellhead equipment, flowlines and processing facilities, are relevant for decisions in the oil and gas industry and in outside regulatory and financial entities.

Petroleum engineers search through endless sources to understand oil and gas chemicals, find problems, and discover solutions while operations are becoming more unconventional and driving towards more sustainable practices. The Oil and Gas Chemistry Management Series brings an all-inclusive suite of tools to cover all the sectors of oil and gas chemicals from drilling to production, processing, storage, and transportation. The second reference in the series, Flow Assurance, delivers the critical chemical oilfield basics while also covering latest research developments and practical solutions. Organized by the type of problems and mitigation methods, this reference allows the engineer to fully understand how to effectively control chemistry issues, make sound decisions, and mitigate challenges ahead. Basics include root cause, model prediction and laboratory simulation of the major chemistry related challenges during oil and gas productions, while more advanced discussions cover the chemical and non-chemical mitigation strategies for more efficient, safe and sustainable operations. Supported by a list of contributing experts from both academia and industry, Flow Assurance brings a necessary reference to bridge petroleum chemistry operations from theory into safer and cost-effective practical applications. Offers full range of oilfield production chemistry issues, including chapters focused on hydrate and organic deposition control, liquid blockage mitigation, and abiotic and microbially influenced corrosion prevention Gain effective control on problems and mitigation strategies from industry list of experts and contributors Delivers both up to date research developments and practical applications, bridging between theory and practice

With easily accessible oil reserves dwindling, petroleum engineers must have a sound understanding of how to access technically challenging resources, especially in the deepwater environment. These technically challenging resources bring with them complexities around fluid flow not normally associated with conventional production systems, and engineers must be knowledgeable about navigating these complexities. Practical Aspects of Flow Assurance in the Petroleum Industry aims to provide practical guidance on all aspects of flow assurance to offer readers a ready reference on how to ensure uninterrupted transport of processed fluids throughout the flow infrastructure by covering all practical aspects of flow assurance, being written in such a way that any engineer dealing with the oil and gas industry will be able to understand the material, containing solved examples on most topics, placing equal emphasis on experimental techniques and modeling methods, and devoting an entire chapter to the analysis and interpretation of published case studies. With its balance of theory and practical applications, this work provides petroleum engineers from a variety of backgrounds with the information needed to maintain and enhance productivity.

Flow assurance solids deposition is one of the main challenges in oil and gas production operations with millions of dollars spent annually on their mitigation. Essentials of Flow Assurance Solids in Oil and Gas Operations works as an all-inclusive reference for engineers and researchers, covering all the different types of solids that are commonly encountered in oil and gas fields. Structured to flow through real-world operations, the reference branches through each solid deposit problem where the root causes are as well as modeling, monitoring, characterization, and management strategies, all comprehensively reviewed in the light of contemporary research breakthroughs. Backed by several field case studies, Essentials of Flow Assurance Solids in Oil and Gas Operations gives petroleum and reservoir engineers a resource to correlate between the theoretical fundamentals and field practical applications allowing for sustainable and optimal operations. Provides the main operations of oil and gas fields, the characteristics of produced fluids, and the main flow assurance challenges Furnishes the basic principles of deposits formation and mitigation, starting with a full investigation of the problems, then mechanisms, causes, predictions, modelling, and sample analysis, followed by management Distinctively discusses the operational and environmental implications of flow assurance solids and their management using chemical and nonchemical methods Teaches engineers through impactful visuals and data sets included in every chapter

Deep Learning for Engineers introduces the fundamental principles of deep learning along with an explanation of the basic elements required for understanding and applying deep learning models. As a comprehensive guideline for applying deep learning models in practical settings, this book features an easy-to-understand coding structure using Python and PyTorch with an in-depth explanation of four typical deep learning case studies on image classification, object detection, semantic segmentation, and image captioning. The fundamentals of convolutional neural network (CNN) and recurrent neural network (RNN) architectures and their practical implementations in science and engineering are also discussed. This book includes exercise problems for all case studies focusing on various fine-tuning approaches in deep learning. Science and engineering students at both undergraduate and graduate levels, academic researchers, and industry professionals will find the contents useful.

Handbook of Multiphase Flow Assurance allows readers to progress in their understanding of basic phenomena and complex operating challenges. The book starts with the fundamentals, but then goes on to discuss phase behavior, fluid sampling, fluid flow properties and fluid characterization. It also covers flow assurance impedance, deliverability, stability and integrity issues, as well as hydraulic, thermal and risk analysis. The inclusion of case studies and references helps provide an industrial focus and practical application that makes the book a novel resource for flow assurance management and an introductory reference for engineers just entering the field of flow assurance. Starts with flow assurance fundamentals, but also includes more complex operating challenges Brings together cross-disciplinary discussions and solutions of flow assurance in a single text Offers case studies and reference guidelines for practical applications