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Probabilistic Oil And Gas Production Forecasting Using Machine Learning
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Download or read book Advanced Computing written by Deepak Garg and published by Springer Nature. This book was released on 2021-02-10 with total page 507 pages. Available in PDF, EPUB and Kindle. Book excerpt: This two-volume set (CCIS 1367-1368) constitutes reviewed and selected papers from the 10th International Advanced Computing Conference, IACC 2020, held in December 2020. The 65 full papers and 2 short papers presented in two volumes were thorougly reviewed and selected from 286 submissions. The papers are organized in the following topical sections: Application of Artificial Intelligence and Machine Learning in Healthcare; Using Natural Language Processing for Solving Text and Language related Applications; Using Different Neural Network Architectures for Interesting applications; Using AI for Plant and Animal related Applications.- Applications of Blockchain and IoT.- Use of Data Science for Building Intelligence Applications; Innovations in Advanced Network Systems; Advanced Algorithms for Miscellaneous Domains; New Approaches in Software Engineering.
Book Synopsis Improved Reservoir Models and Production Forecasting Techniques for Multi-Stage Fractured Hydrocarbon Wells by : Ruud Weijermars
Download or read book Improved Reservoir Models and Production Forecasting Techniques for Multi-Stage Fractured Hydrocarbon Wells written by Ruud Weijermars and published by MDPI. This book was released on 2019-12-12 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: The massive increase in energy demand and the related rapid development of unconventional reservoirs has opened up exciting new energy supply opportunities along with new, seemingly intractable engineering and research challenges. The energy industry has primarily depended on a heuristic approach—rather than a systematic approach—to optimize and tackle the various challenges when developing new and improving the performance of existing unconventional reservoirs. Industry needs accurate estimations of well production performance and of the cumulative estimated ultimate reserves, accounting for uncertainty. This Special Issue presents 10 original and high-quality research articles related to the modeling of unconventional reservoirs, which showcase advanced methods for fractured reservoir simulation, and improved production forecasting techniques.
Download or read book MATLAB Deep Learning written by Phil Kim and published by Apress. This book was released on 2017-06-15 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Applications of Artificial Intelligence (AI) and Machine Learning (ML) in the Petroleum Industry by : Manan Shah
Download or read book Applications of Artificial Intelligence (AI) and Machine Learning (ML) in the Petroleum Industry written by Manan Shah and published by CRC Press. This book was released on 2022-09-02 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: Today, raw data on any industry is widely available. With the help of artificial intelligence (AI) and machine learning (ML), this data can be used to gain meaningful insights. In addition, as data is the new raw material for today’s world, AI and ML will be applied in every industrial sector. Industry 4.0 mainly focuses on the automation of things. From that perspective, the oil and gas industry is one of the largest industries in terms of economy and energy. Applications of Artificial Intelligence (AI) and Machine Learning (ML) in the Petroleum Industry analyzes the use of AI and ML in the oil and gas industry across all three sectors, namely upstream, midstream, and downstream. It covers every aspect of the petroleum industry as related to the application of AI and ML, ranging from exploration, data management, extraction, processing, real-time data analysis, monitoring, cloud-based connectivity system, and conditions analysis, to the final delivery of the product to the end customer, while taking into account the incorporation of the safety measures for a better operation and the efficient and effective execution of operations. This book explores the variety of applications that can be integrated to support the existing petroleum and adjacent sectors to solve industry problems. It will serve as a useful guide for professionals working in the petroleum industry, industrial engineers, AI and ML experts and researchers, as well as students.
Book Synopsis Forecasting with Artificial Intelligence by : Mohsen Hamoudia
Download or read book Forecasting with Artificial Intelligence written by Mohsen Hamoudia and published by Springer Nature. This book was released on 2023-10-22 with total page 441 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a comprehensive guide that explores the intersection of artificial intelligence and forecasting, providing the latest insights and trends in this rapidly evolving field. The book contains fourteen chapters covering a wide range of topics, including the concept of AI, its impact on economic decision-making, traditional and machine learning-based forecasting methods, challenges in demand forecasting, global forecasting models, meta-learning and feature-based forecasting, ensembling, deep learning, scalability in industrial and optimization applications, and forecasting performance evaluation. With key illustrations, state-of-the-art implementations, best practices, and notable advances, this book offers practical insights into the theory and practice of AI-based forecasting. This book is a valuable resource for anyone involved in forecasting, including forecasters, statisticians, data scientists, business analysts, or decision-makers.
Book Synopsis Data Analytics in Reservoir Engineering by : Sathish Sankaran
Download or read book Data Analytics in Reservoir Engineering written by Sathish Sankaran and published by . This book was released on 2020-10-29 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Analytics in Reservoir Engineering describes the relevance of data analytics for the oil and gas industry, with particular emphasis on reservoir engineering.
Book Synopsis Machine Learning and Flow Assurance in Oil and Gas Production by : Bhajan Lal
Download or read book Machine Learning and Flow Assurance in Oil and Gas Production written by Bhajan Lal and published by Springer Nature. This book was released on 2023-03-11 with total page 179 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Assisted History Matching for Unconventional Reservoirs by : Sutthaporn Tripoppoom
Download or read book Assisted History Matching for Unconventional Reservoirs written by Sutthaporn Tripoppoom and published by Gulf Professional Publishing. This book was released on 2021-08-05 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: As unconventional reservoir activity grows in demand, reservoir engineers relying on history matching are challenged with this time-consuming task in order to characterize hydraulic fracture and reservoir properties, which are expensive and difficult to obtain. Assisted History Matching for Unconventional Reservoirs delivers a critical tool for today's engineers proposing an Assisted History Matching (AHM) workflow. The AHM workflow has benefits of quantifying uncertainty without bias or being trapped in any local minima and this reference helps the engineer integrate an efficient and non-intrusive model for fractures that work with any commercial simulator. Additional benefits include various applications of field case studies such as the Marcellus shale play and visuals on the advantages and disadvantages of alternative models. Rounding out with additional references for deeper learning, Assisted History Matching for Unconventional Reservoirs gives reservoir engineers a holistic view on how to model today's fractures and unconventional reservoirs. - Provides understanding on simulations for hydraulic fractures, natural fractures, and shale reservoirs using embedded discrete fracture model (EDFM) - Reviews automatic and assisted history matching algorithms including visuals on advantages and limitations of each model - Captures data on uncertainties of fractures and reservoir properties for better probabilistic production forecasting and well placement
Book Synopsis From Industry 4.0 to Industry 5.0 by : Allam Hamdan
Download or read book From Industry 4.0 to Industry 5.0 written by Allam Hamdan and published by Springer Nature. This book was released on 2023-07-31 with total page 1022 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims at bringing together global researchers to generate thought on how this transition from Industry 4.0 to Industry 5.0 could make a difference to the globe for larger good. The collaboration and interaction between man and machine has given rise to Industry 5.0. With the prime objective of Industry 5.0 to create a benefit for the human beings while tapping on to the advantage of Industry 4.0, in no case, does it replace what has already been achieved. In fact, it brings to light what can be done in order to make life better. While Industry 4.0 offered extraordinary technological advancement, Industry 5.0 reasons out that technology alone is not sufficient to answer everything or provide a solution, but it is an amalgamation of both machine and human interaction to create that difference. In fact, with the impact of widespread digitalization that has led to dehumanization of the industrial makeup, the interest of global researchers has increased toward mapping how the human creativity and brainpower can be reconciled with the intelligent systems that can enhance process efficiency. Industry 5.0 has touched upon some of those key domains which are of much concern and debate globally including resilience (both business and cyber), environment and sustainability, diversity and inclusion, values and ethics, vision and purpose, circular economy, understanding the human–machine collaboration and the ‘human-touch’ in the production process. This transition that has taken place in moving from Industry 4.0 to Industry 5.0 has essentially created a need to pay cognizance to the role of ‘human’ in the process which creates an enhanced focus toward the right kind of skills and competencies, identification of training and developmental needs, talent acquisition and management, safety and wellbeing, future of work as well as hybrid working models. Undeniably, the pace with which Industry 4.0 has been accelerating has bypassed the first three industrial revolutions, which is definitely a consequence of the fast introduction of new and cutting-edge technologies. While organizations are already in analyzing the context, mapping this transition and the flow of activities from Industry 4.0 to 5.0 is gaining attention as Industry 4.0 lacked personalization and customization. This co-existence of man and machine creates a pathway for newer prospects and opportunities to emerge and expand possibilities of personalization with the empowerment of ‘human’ in the production process. This lays the foundation for this book. This book adopts a forward-looking approach by bringing in research and contributions that facilitate in mapping the consereasons, consequences and solutions for ‘man+machine’ across industries. This book serves as a guide not just to academia but also to the industry to adopt suitable strategies that offer insights into global best practices as well as the innovations in the domain.
Book Synopsis Proceedings of the International Field Exploration and Development Conference 2020 by : Jia'en Lin
Download or read book Proceedings of the International Field Exploration and Development Conference 2020 written by Jia'en Lin and published by Springer Nature. This book was released on 2021-06-17 with total page 3487 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a compilation of selected papers from the 10th International Field Exploration and Development Conference (IFEDC 2020). The proceedings focuses on Reservoir Surveillance and Management, Reservoir Evaluation and Dynamic Description, Reservoir Production Stimulation and EOR, Ultra-Tight Reservoir, Unconventional Oil and Gas Resources Technology, Oil and Gas Well Production Testing, Geomechanics. The conference not only provides a platform to exchanges experience, but also promotes the development of scientific research in oil & gas exploration and production. The main audience for the work includes reservoir engineer, geological engineer, enterprise managers senior engineers as well as professional students.
Book Synopsis Hydraulic Fracturing in Unconventional Reservoirs by : Hoss Belyadi
Download or read book Hydraulic Fracturing in Unconventional Reservoirs written by Hoss Belyadi and published by Gulf Professional Publishing. This book was released on 2019-06-18 with total page 636 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hydraulic Fracturing in Unconventional Reservoirs: Theories, Operations, and Economic Analysis, Second Edition, presents the latest operations and applications in all facets of fracturing. Enhanced to include today's newest technologies, such as machine learning and the monitoring of field performance using pressure and rate transient analysis, this reference gives engineers the full spectrum of information needed to run unconventional field developments. Covering key aspects, including fracture clean-up, expanded material on refracturing, and a discussion on economic analysis in unconventional reservoirs, this book keeps today's petroleum engineers updated on the critical aspects of unconventional activity. - Helps readers understand drilling and production technology and operations in shale gas through real-field examples - Covers various topics on fractured wells and the exploitation of unconventional hydrocarbons in one complete reference - Presents the latest operations and applications in all facets of fracturing
Book Synopsis Practical Probabilistic Programming by : Avi Pfeffer
Download or read book Practical Probabilistic Programming written by Avi Pfeffer and published by Simon and Schuster. This book was released on 2016-03-29 with total page 650 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Practical Probabilistic Programming introduces the working programmer to probabilistic programming. In it, you'll learn how to use the PP paradigm to model application domains and then express those probabilistic models in code. Although PP can seem abstract, in this book you'll immediately work on practical examples, like using the Figaro language to build a spam filter and applying Bayesian and Markov networks, to diagnose computer system data problems and recover digital images. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology The data you accumulate about your customers, products, and website users can help you not only to interpret your past, it can also help you predict your future! Probabilistic programming uses code to draw probabilistic inferences from data. By applying specialized algorithms, your programs assign degrees of probability to conclusions. This means you can forecast future events like sales trends, computer system failures, experimental outcomes, and many other critical concerns. About the Book Practical Probabilistic Programming introduces the working programmer to probabilistic programming. In this book, you’ll immediately work on practical examples like building a spam filter, diagnosing computer system data problems, and recovering digital images. You’ll discover probabilistic inference, where algorithms help make extended predictions about issues like social media usage. Along the way, you’ll learn to use functional-style programming for text analysis, object-oriented models to predict social phenomena like the spread of tweets, and open universe models to gauge real-life social media usage. The book also has chapters on how probabilistic models can help in decision making and modeling of dynamic systems. What's Inside Introduction to probabilistic modeling Writing probabilistic programs in Figaro Building Bayesian networks Predicting product lifecycles Decision-making algorithms About the Reader This book assumes no prior exposure to probabilistic programming. Knowledge of Scala is helpful. About the Author Avi Pfeffer is the principal developer of the Figaro language for probabilistic programming. Table of Contents PART 1 INTRODUCING PROBABILISTIC PROGRAMMING AND FIGARO Probabilistic programming in a nutshell A quick Figaro tutorial Creating a probabilistic programming application PART 2 WRITING PROBABILISTIC PROGRAMS Probabilistic models and probabilistic programs Modeling dependencies with Bayesian and Markov networks Using Scala and Figaro collections to build up models Object-oriented probabilistic modeling Modeling dynamic systems PART 3 INFERENCE The three rules of probabilistic inference Factored inference algorithms Sampling algorithms Solving other inference tasks Dynamic reasoning and parameter learning
Book Synopsis Artificial Intelligent Approaches in Petroleum Geosciences by : Constantin Cranganu
Download or read book Artificial Intelligent Approaches in Petroleum Geosciences written by Constantin Cranganu and published by Springer Nature. This book was released on with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Novel Financial Applications of Machine Learning and Deep Learning by : Mohammad Zoynul Abedin
Download or read book Novel Financial Applications of Machine Learning and Deep Learning written by Mohammad Zoynul Abedin and published by Springer Nature. This book was released on 2023-03-01 with total page 235 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the state-of-the-art applications of machine learning in the finance domain with a focus on financial product modeling, which aims to advance the model performance and minimize risk and uncertainty. It provides both practical and managerial implications of financial and managerial decision support systems which capture a broad range of financial data traits. It also serves as a guide for the implementation of risk-adjusted financial product pricing systems, while adding a significant supplement to the financial literacy of the investigated study. The book covers advanced machine learning techniques, such as Support Vector Machine, Neural Networks, Random Forest, K-Nearest Neighbors, Extreme Learning Machine, Deep Learning Approaches, and their application to finance datasets. It also leverages real-world financial instances to practice business product modeling and data analysis. Software code, such as MATLAB, Python and/or R including datasets within a broad range of financial domain are included for more rigorous practice. The book primarily aims at providing graduate students and researchers with a roadmap for financial data analysis. It is also intended for a broad audience, including academics, professional financial analysts, and policy-makers who are involved in forecasting, modeling, trading, risk management, economics, credit risk, and portfolio management.
Book Synopsis Achievements and New Frontiers in Research Oriented to Earthquake Forecasting by : Giovanni Martinelli
Download or read book Achievements and New Frontiers in Research Oriented to Earthquake Forecasting written by Giovanni Martinelli and published by Frontiers Media SA. This book was released on 2022-06-23 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cover Image Credit: Zhaofei Liu and Ying Li From the Institute of Earthquake Forecasting, China
Book Synopsis Fundamentals of Deep Learning by : Nikhil Buduma
Download or read book Fundamentals of Deep Learning written by Nikhil Buduma and published by "O'Reilly Media, Inc.". This book was released on 2017-05-25 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the reinvigoration of neural networks in the 2000s, deep learning has become an extremely active area of research, one that’s paving the way for modern machine learning. In this practical book, author Nikhil Buduma provides examples and clear explanations to guide you through major concepts of this complicated field. Companies such as Google, Microsoft, and Facebook are actively growing in-house deep-learning teams. For the rest of us, however, deep learning is still a pretty complex and difficult subject to grasp. If you’re familiar with Python, and have a background in calculus, along with a basic understanding of machine learning, this book will get you started. Examine the foundations of machine learning and neural networks Learn how to train feed-forward neural networks Use TensorFlow to implement your first neural network Manage problems that arise as you begin to make networks deeper Build neural networks that analyze complex images Perform effective dimensionality reduction using autoencoders Dive deep into sequence analysis to examine language Learn the fundamentals of reinforcement learning
Book Synopsis Reservoir Characterization by : Fred Aminzadeh
Download or read book Reservoir Characterization written by Fred Aminzadeh and published by John Wiley & Sons. This book was released on 2022-01-06 with total page 578 pages. Available in PDF, EPUB and Kindle. Book excerpt: RESERVOIR CHARACTERIZATION The second volume in the series, “Sustainable Energy Engineering,” written by some of the foremost authorities in the world on reservoir engineering, this groundbreaking new volume presents the most comprehensive and updated new processes, equipment, and practical applications in the field. Long thought of as not being “sustainable,” newly discovered sources of petroleum and newly developed methods for petroleum extraction have made it clear that not only can the petroleum industry march toward sustainability, but it can be made “greener” and more environmentally friendly. Sustainable energy engineering is where the technical, economic, and environmental aspects of energy production intersect and affect each other. This collection of papers covers the strategic and economic implications of methods used to characterize petroleum reservoirs. Born out of the journal by the same name, formerly published by Scrivener Publishing, most of the articles in this volume have been updated, and there are some new additions, as well, to keep the engineer abreast of any updates and new methods in the industry. Truly a snapshot of the state of the art, this groundbreaking volume is a must-have for any petroleum engineer working in the field, environmental engineers, petroleum engineering students, and any other engineer or scientist working with reservoirs. This outstanding new volume: Is a collection of papers on reservoir characterization written by world-renowned engineers and scientists and presents them here, in one volume Contains in-depth coverage of not just the fundamentals of reservoir characterization, but the anomalies and challenges, set in application-based, real-world situations Covers reservoir characterization for the engineer to be able to solve daily problems on the job, whether in the field or in the office Deconstructs myths that are prevalent and deeply rooted in the industry and reconstructs logical solutions Is a valuable resource for the veteran engineer, new hire, or petroleum engineering student
