Applications of Artificial Intelligence Techniques in the Petroleum Industry

Applications of Artificial Intelligence Techniques in the Petroleum Industry
Author: Abdolhossein Hemmati Sarapardeh,Aydin Larestani,Nait Amar Menad,Sassan Hajirezaie
Publsiher: Gulf Professional Publishing
Total Pages: 322
Release: 2020-08-26
ISBN 10: 0128223855
ISBN 13: 9780128223857
Language: EN, FR, DE, ES & NL

Applications of Artificial Intelligence Techniques in the Petroleum Industry Book Review:

Applications of Artificial Intelligence Techniques in the Petroleum Industry gives engineers a critical resource to help them understand the machine learning that will solve specific engineering challenges. The reference begins with fundamentals, covering preprocessing of data, types of intelligent models, and training and optimization algorithms. The book moves on to methodically address artificial intelligence technology and applications by the upstream sector, covering exploration, drilling, reservoir and production engineering. Final sections cover current gaps and future challenges. Teaches how to apply machine learning algorithms that work best in exploration, drilling, reservoir or production engineering Helps readers increase their existing knowledge on intelligent data modeling, machine learning and artificial intelligence, with foundational chapters covering the preprocessing of data and training on algorithms Provides tactics on how to cover complex projects such as shale gas, tight oils, and other types of unconventional reservoirs with more advanced model input

Artificial Intelligent Approaches in Petroleum Geosciences

Artificial Intelligent Approaches in Petroleum Geosciences
Author: Constantin Cranganu,Henri Luchian,Mihaela Elena Breaban
Publsiher: Springer
Total Pages: 290
Release: 2015-04-20
ISBN 10: 3319165313
ISBN 13: 9783319165318
Language: EN, FR, DE, ES & NL

Artificial Intelligent Approaches in Petroleum Geosciences Book Review:

This book presents several intelligent approaches for tackling and solving challenging practical problems facing those in the petroleum geosciences and petroleum industry. Written by experienced academics, this book offers state-of-the-art working examples and provides the reader with exposure to the latest developments in the field of intelligent methods applied to oil and gas research, exploration and production. It also analyzes the strengths and weaknesses of each method presented using benchmarking, whilst also emphasizing essential parameters such as robustness, accuracy, speed of convergence, computer time, overlearning and the role of normalization. The intelligent approaches presented include artificial neural networks, fuzzy logic, active learning method, genetic algorithms and support vector machines, amongst others. Integration, handling data of immense size and uncertainty, and dealing with risk management are among crucial issues in petroleum geosciences. The problems we have to solve in this domain are becoming too complex to rely on a single discipline for effective solutions and the costs associated with poor predictions (e.g. dry holes) increase. Therefore, there is a need to establish a new approach aimed at proper integration of disciplines (such as petroleum engineering, geology, geophysics and geochemistry), data fusion, risk reduction and uncertainty management. These intelligent techniques can be used for uncertainty analysis, risk assessment, data fusion and mining, data analysis and interpretation, and knowledge discovery, from diverse data such as 3-D seismic, geological data, well logging, and production data. This book is intended for petroleum scientists, data miners, data scientists and professionals and post-graduate students involved in petroleum industry.

Machine Learning in the Oil and Gas Industry

Machine Learning in the Oil and Gas Industry
Author: Yogendra Narayan Pandey,Ayush Rastogi,Sribharath Kainkaryam,Srimoyee Bhattacharya,Luigi Saputelli
Publsiher: Apress
Total Pages: 300
Release: 2020-11-03
ISBN 10: 9781484260937
ISBN 13: 1484260937
Language: EN, FR, DE, ES & NL

Machine Learning in the Oil and Gas Industry Book Review:

Apply machine and deep learning to solve some of the challenges in the oil and gas industry. The book begins with a brief discussion of the oil and gas exploration and production life cycle in the context of data flow through the different stages of industry operations. This leads to a survey of some interesting problems, which are good candidates for applying machine and deep learning approaches. The initial chapters provide a primer on the Python programming language used for implementing the algorithms; this is followed by an overview of supervised and unsupervised machine learning concepts. The authors provide industry examples using open source data sets along with practical explanations of the algorithms, without diving too deep into the theoretical aspects of the algorithms employed. Machine Learning in the Oil and Gas Industry covers problems encompassing diverse industry topics, including geophysics (seismic interpretation), geological modeling, reservoir engineering, and production engineering. Throughout the book, the emphasis is on providing a practical approach with step-by-step explanations and code examples for implementing machine and deep learning algorithms for solving real-life problems in the oil and gas industry. What You Will Learn Understanding the end-to-end industry life cycle and flow of data in the industrial operations of the oil and gas industry Get the basic concepts of computer programming and machine and deep learning required for implementing the algorithms used Study interesting industry problems that are good candidates for being solved by machine and deep learning Discover the practical considerations and challenges for executing machine and deep learning projects in the oil and gas industry Who This Book Is For Professionals in the oil and gas industry who can benefit from a practical understanding of the machine and deep learning approach to solving real-life problems.

Artificial Intelligence in the Petroleum Industry

Artificial Intelligence in the Petroleum Industry
Author: Bertrand Braunschweig
Publsiher: Editions TECHNIP
Total Pages: 381
Release: 1996
ISBN 10: 9782710807032
ISBN 13: 2710807033
Language: EN, FR, DE, ES & NL

Artificial Intelligence in the Petroleum Industry Book Review:

Intelligent Digital Oil and Gas Fields

Intelligent Digital Oil and Gas Fields
Author: Gustavo Carvajal,Marko Maucec,Stan Cullick
Publsiher: Gulf Professional Publishing
Total Pages: 374
Release: 2017-12-14
ISBN 10: 012804747X
ISBN 13: 9780128047477
Language: EN, FR, DE, ES & NL

Intelligent Digital Oil and Gas Fields Book Review:

Intelligent Digital Oil and Gas Fields: Concepts, Collaboration, and Right-time Decisions delivers to the reader a roadmap through the fast-paced changes in the digital oil field landscape of technology in the form of new sensors, well mechanics such as downhole valves, data analytics and models for dealing with a barrage of data, and changes in the way professionals collaborate on decisions. The book introduces the new age of digital oil and gas technology and process components and provides a backdrop to the value and experience industry has achieved from these in the last few years. The book then takes the reader on a journey first at a well level through instrumentation and measurement for real-time data acquisition, and then provides practical information on analytics on the real-time data. Artificial intelligence techniques provide insights from the data. The road then travels to the "integrated asset" by detailing how companies utilize Integrated Asset Models to manage assets (reservoirs) within DOF context. From model to practice, new ways to operate smart wells enable optimizing the asset. Intelligent Digital Oil and Gas Fields is packed with examples and lessons learned from various case studies and provides extensive references for further reading and a final chapter on the "next generation digital oil field," e.g., cloud computing, big data analytics and advances in nanotechnology. This book is a reference that can help managers, engineers, operations, and IT experts understand specifics on how to filter data to create useful information, address analytics, and link workflows across the production value chain enabling teams to make better decisions with a higher degree of certainty and reduced risk. Covers multiple examples and lessons learned from a variety of reservoirs from around the world and production situations Includes techniques on change management and collaboration Delivers real and readily applicable knowledge on technical equipment, workflows and data challenges such as acquisition and quality control that make up the digital oil and gas field solutions of today Describes collaborative systems and ways of working and how companies are transitioning work force to use the technology and making more optimal decisions

Machine Learning and Data Science in the Oil and Gas Industry

Machine Learning and Data Science in the Oil and Gas Industry
Author: Patrick Bangert
Publsiher: Gulf Professional Publishing
Total Pages: 300
Release: 2021-03-15
ISBN 10: 9780128207147
ISBN 13: 0128207140
Language: EN, FR, DE, ES & NL

Machine Learning and Data Science in the Oil and Gas Industry Book Review:

Machine Learning and Data Science in the Oil and Gas Industry explains how machine learning can be specifically tailored to oil and gas use cases. Petroleum engineers will learn when to use machine learning, how it is already used in oil and gas operations, and how to manage the data stream moving forward. Practical in its approach, the book explains all aspects of a data science or machine learning project, including the managerial parts of it that are so often the cause for failure. Several real-life case studies round out the book with topics such as predictive maintenance, soft sensing, and forecasting. Viewed as a guide book, this manual will lead a practitioner through the journey of a data science project in the oil and gas industry circumventing the pitfalls and articulating the business value. Chart an overview of the techniques and tools of machine learning including all the non-technological aspects necessary to be successful Gain practical understanding of machine learning used in oil and gas operations through contributed case studies Learn change management skills that will help gain confidence in pursuing the technology Understand the workflow of a full-scale project and where machine learning benefits (and where it does not)

Artificial Intelligence

Artificial Intelligence
Author: Marco Antonio Aceves-Fernandez
Publsiher: BoD – Books on Demand
Total Pages: 464
Release: 2018-06-27
ISBN 10: 178923364X
ISBN 13: 9781789233643
Language: EN, FR, DE, ES & NL

Artificial Intelligence Book Review:

Artificial intelligence (AI) is taking an increasingly important role in our society. From cars, smartphones, airplanes, consumer applications, and even medical equipment, the impact of AI is changing the world around us. The ability of machines to demonstrate advanced cognitive skills in taking decisions, learn and perceive the environment, predict certain behavior, and process written or spoken languages, among other skills, makes this discipline of paramount importance in today's world. Although AI is changing the world for the better in many applications, it also comes with its challenges. This book encompasses many applications as well as new techniques, challenges, and opportunities in this fascinating area.

Proceedings of the Second Workshop Application of Artificial Intelligence Techniques in Seismology and Engineering Seismology

Proceedings of the Second Workshop  Application of Artificial Intelligence Techniques in Seismology and Engineering Seismology
Author: Mariano Garcia-Fernandez,Gaetano Zonno
Publsiher: Centre Europeen de Geodynamique Et de Seismologie
Total Pages: 304
Release: 1996
ISBN 10:
ISBN 13: STANFORD:36105112846261
Language: EN, FR, DE, ES & NL

Proceedings of the Second Workshop Application of Artificial Intelligence Techniques in Seismology and Engineering Seismology Book Review:

Computational Intelligence

Computational Intelligence
Author: Andries P. Engelbrecht
Publsiher: John Wiley & Sons
Total Pages: 628
Release: 2007-10-22
ISBN 10: 9780470512500
ISBN 13: 0470512504
Language: EN, FR, DE, ES & NL

Computational Intelligence Book Review:

Computational Intelligence: An Introduction, Second Edition offers an in-depth exploration into the adaptive mechanisms that enable intelligent behaviour in complex and changing environments. The main focus of this text is centred on the computational modelling of biological and natural intelligent systems, encompassing swarm intelligence, fuzzy systems, artificial neutral networks, artificial immune systems and evolutionary computation. Engelbrecht provides readers with a wide knowledge of Computational Intelligence (CI) paradigms and algorithms; inviting readers to implement and problem solve real-world, complex problems within the CI development framework. This implementation framework will enable readers to tackle new problems without any difficulty through a single Java class as part of the CI library. Key features of this second edition include: A tutorial, hands-on based presentation of the material. State-of-the-art coverage of the most recent developments in computational intelligence with more elaborate discussions on intelligence and artificial intelligence (AI). New discussion of Darwinian evolution versus Lamarckian evolution, also including swarm robotics, hybrid systems and artificial immune systems. A section on how to perform empirical studies; topics including statistical analysis of stochastic algorithms, and an open source library of CI algorithms. Tables, illustrations, graphs, examples, assignments, Java code implementing the algorithms, and a complete CI implementation and experimental framework. Computational Intelligence: An Introduction, Second Edition is essential reading for third and fourth year undergraduate and postgraduate students studying CI. The first edition has been prescribed by a number of overseas universities and is thus a valuable teaching tool. In addition, it will also be a useful resource for researchers in Computational Intelligence and Artificial Intelligence, as well as engineers, statisticians, operational researchers, and bioinformaticians with an interest in applying AI or CI to solve problems in their domains. Check out http://www.ci.cs.up.ac.za for examples, assignments and Java code implementing the algorithms.

Data Mining

Data Mining
Author: Georg Zangl
Publsiher: Unknown
Total Pages: 222
Release: 2003
ISBN 10:
ISBN 13: STANFORD:36105119949589
Language: EN, FR, DE, ES & NL

Data Mining Book Review:

Emerging Intelligent Technologies in Industry

Emerging Intelligent Technologies in Industry
Author: Dominik Ryżko,Piotr Gawrysiak,Henryk Rybinski,Marzena Kryszkiewicz
Publsiher: Springer
Total Pages: 344
Release: 2011-08-31
ISBN 10: 3642227325
ISBN 13: 9783642227325
Language: EN, FR, DE, ES & NL

Emerging Intelligent Technologies in Industry Book Review:

Intelligent technologies are the essential factors of innovation, and enable the industry to overcome technological limitations and explore the new frontiers. Therefore it is necessary for scientists and practitioners to cooperate and inspire each other, and use the latest research results in creating new designs and products. The idea of this book came out with the industrial workshop organized at the ISMIS conference in Warsaw, 2011. The book covers several applications of emerging, intelligent technologies in various branches of the industry. The contributions describe modern intelligent tools, algorithms and architectures, which have the potential to solve real problems, experienced by practitioners in various industry sectors. We hope this volume will show new directions for cooperation between science and industry and will facilitate efficient transfer of knowledge in the area of intelligent information systems.

Shale Analytics

Shale Analytics
Author: Shahab D. Mohaghegh
Publsiher: Springer
Total Pages: 287
Release: 2017-02-09
ISBN 10: 3319487531
ISBN 13: 9783319487533
Language: EN, FR, DE, ES & NL

Shale Analytics Book Review:

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.

Explorations in Parallel Distributed Processing

Explorations in Parallel Distributed Processing
Author: James L. McClelland,David E. Rumelhart
Publsiher: MIT Press
Total Pages: 355
Release: 1989
ISBN 10: 9780262631297
ISBN 13: 0262631296
Language: EN, FR, DE, ES & NL

Explorations in Parallel Distributed Processing Book Review:

Includes 2 diskettes (for the Macintosh)

Industrial AI

Industrial AI
Author: Jay Lee
Publsiher: Springer Nature
Total Pages: 162
Release: 2020-02-07
ISBN 10: 9811521441
ISBN 13: 9789811521447
Language: EN, FR, DE, ES & NL

Industrial AI Book Review:

This book introduces Industrial AI in multiple dimensions. Industrial AI is a systematic discipline which focuses on developing, validating and deploying various machine learning algorithms for industrial applications with sustainable performance. Combined with the state-of-the-art sensing, communication and big data analytics platforms, a systematic Industrial AI methodology will allow integration of physical systems with computational models. The concept of Industrial AI is in infancy stage and may encompass the collective use of technologies such as Internet of Things, Cyber-Physical Systems and Big Data Analytics under the Industry 4.0 initiative where embedded computing devices, smart objects and the physical environment interact with each other to reach intended goals. A broad range of Industries including automotive, aerospace, healthcare, semiconductors, energy, transportation, mining, construction, and industrial automation could harness the power of Industrial AI to gain insights into the invisible relationship of the operation conditions and further use that insight to optimize their uptime, productivity and efficiency of their operations. In terms of predictive maintenance, Industrial AI can detect incipient changes in the system and predict the remains useful life and further to optimize maintenance tasks to avoid disruption to operations.

Competing in the Age of AI

Competing in the Age of AI
Author: Marco Iansiti,Karim R. Lakhani
Publsiher: Harvard Business Press
Total Pages: 288
Release: 2020-01-07
ISBN 10: 1633697630
ISBN 13: 9781633697638
Language: EN, FR, DE, ES & NL

Competing in the Age of AI Book Review:

"a provocative new book" -- The New York Times AI-centric organizations exhibit a new operating architecture, redefining how they create, capture, share, and deliver value. Marco Iansiti and Karim R. Lakhani show how reinventing the firm around data, analytics, and AI removes traditional constraints on scale, scope, and learning that have restricted business growth for hundreds of years. From Airbnb to Ant Financial, Microsoft to Amazon, research shows how AI-driven processes are vastly more scalable than traditional processes, allow massive scope increase, enabling companies to straddle industry boundaries, and create powerful opportunities for learning--to drive ever more accurate, complex, and sophisticated predictions. When traditional operating constraints are removed, strategy becomes a whole new game, one whose rules and likely outcomes this book will make clear. Iansiti and Lakhani: Present a framework for rethinking business and operating models Explain how "collisions" between AI-driven/digital and traditional/analog firms are reshaping competition, altering the structure of our economy, and forcing traditional companies to rearchitect their operating models Explain the opportunities and risks created by digital firms Describe the new challenges and responsibilities for the leaders of both digital and traditional firms Packed with examples--including many from the most powerful and innovative global, AI-driven competitors--and based on research in hundreds of firms across many sectors, this is your essential guide for rethinking how your firm competes and operates in the era of AI.

Applications and Innovations in Intelligent Systems VII

Applications and Innovations in Intelligent Systems VII
Author: Richard Ellis
Publsiher: Springer
Total Pages: 345
Release: 2000-01-04
ISBN 10:
ISBN 13: UOM:39015049649059
Language: EN, FR, DE, ES & NL

Applications and Innovations in Intelligent Systems VII Book Review:

Following on from a three-year knowledge management project, seven organisations formed aco-operative group for knowledge management. This group meets through the Knowledge Management Implementers Forum (KMIF). Each of the organisations participating in this work are, by implication, interested in the development of KM. The aims of the forum are t9 exchange ideas and share experience in the areaofknowledge management. The organisations involved are: ~ British Aerospace (Samlesbury) ~ ICI ~ ICL ~ North WestWater ~ IDS Cad-Graphics ~ Liverpool John Moores University ~ NWAIAG (Blackburn College) 1.1 The Organisations Involved Each ofthe organisations has specific reasons for being involved in this project and in KM. The British Aerospace Samlesbury site is a large manufacturing site employing ground breaking technology for Europe's front line military aircraft. The factory works with a well-managed supply chain and works closely with other British Aerospace sites in the manufacture of aircraft components. It has set up a partnership with another Aerospace Company based on exchange of knowledge and therefore needs to value that knowledge. ICI is one of the UK's leading chemical companies and plays on an international stage. Changes in international supply and demand require ICI to respond quickly to market pressures. This means that the company needs to use its knowledge assets in a well managed way and put systems in place that increase the flexibility and ensure the security ofthese important assets.

Reservoir Geomechanics

Reservoir Geomechanics
Author: Mark D. Zoback
Publsiher: Cambridge University Press
Total Pages: 329
Release: 2010-04-01
ISBN 10: 1107320089
ISBN 13: 9781107320086
Language: EN, FR, DE, ES & NL

Reservoir Geomechanics Book Review:

This interdisciplinary book encompasses the fields of rock mechanics, structural geology and petroleum engineering to address a wide range of geomechanical problems that arise during the exploitation of oil and gas reservoirs. It considers key practical issues such as prediction of pore pressure, estimation of hydrocarbon column heights and fault seal potential, determination of optimally stable well trajectories, casing set points and mud weights, changes in reservoir performance during depletion, and production-induced faulting and subsidence. The book establishes the basic principles involved before introducing practical measurement and experimental techniques to improve recovery and reduce exploitation costs. It illustrates their successful application through case studies taken from oil and gas fields around the world. This book is a practical reference for geoscientists and engineers in the petroleum and geothermal industries, and for research scientists interested in stress measurements and their application to problems of faulting and fluid flow in the crust.

Artificial Intelligence and Applied Mathematics in Engineering Problems

Artificial Intelligence and Applied Mathematics in Engineering Problems
Author: D. Jude Hemanth,Utku Kose
Publsiher: Springer Nature
Total Pages: 1081
Release: 2020-01-03
ISBN 10: 3030361780
ISBN 13: 9783030361785
Language: EN, FR, DE, ES & NL

Artificial Intelligence and Applied Mathematics in Engineering Problems Book Review:

This book features research presented at the 1st International Conference on Artificial Intelligence and Applied Mathematics in Engineering, held on 20–22 April 2019 at Antalya, Manavgat (Turkey). In today’s world, various engineering areas are essential components of technological innovations and effective real-world solutions for a better future. In this context, the book focuses on problems in engineering and discusses research using artificial intelligence and applied mathematics. Intended for scientists, experts, M.Sc. and Ph.D. students, postdocs and anyone interested in the subjects covered, the book can also be used as a reference resource for courses related to artificial intelligence and applied mathematics.

Machine Learning for Subsurface Characterization

Machine Learning for Subsurface Characterization
Author: Siddharth Misra,Hao Li,Jiabo He
Publsiher: Gulf Professional Publishing
Total Pages: 440
Release: 2019-10-12
ISBN 10: 0128177373
ISBN 13: 9780128177372
Language: EN, FR, DE, ES & NL

Machine Learning for Subsurface Characterization Book Review:

Machine Learning for Subsurface Characterization develops and applies neural networks, random forests, deep learning, unsupervised learning, Bayesian frameworks, and clustering methods for subsurface characterization. Machine learning (ML) focusses on developing computational methods/algorithms that learn to recognize patterns and quantify functional relationships by processing large data sets, also referred to as the "big data." Deep learning (DL) is a subset of machine learning that processes "big data" to construct numerous layers of abstraction to accomplish the learning task. DL methods do not require the manual step of extracting/engineering features; however, it requires us to provide large amounts of data along with high-performance computing to obtain reliable results in a timely manner. This reference helps the engineers, geophysicists, and geoscientists get familiar with data science and analytics terminology relevant to subsurface characterization and demonstrates the use of data-driven methods for outlier detection, geomechanical/electromagnetic characterization, image analysis, fluid saturation estimation, and pore-scale characterization in the subsurface. Learn from 13 practical case studies using field, laboratory, and simulation data Become knowledgeable with data science and analytics terminology relevant to subsurface characterization Learn frameworks, concepts, and methods important for the engineer’s and geoscientist’s toolbox needed to support

Lost Circulation

Lost Circulation
Author: Alexandre Lavrov
Publsiher: Gulf Professional Publishing
Total Pages: 264
Release: 2016-03-16
ISBN 10: 0128039418
ISBN 13: 9780128039410
Language: EN, FR, DE, ES & NL

Lost Circulation Book Review:

Lost Circulation: Mechanisms and Solutions provides the latest information on a long-existing problem for drilling and cementing engineers that can cause improper drilling conditions, safety risks, and annual losses of millions of wasted dollars for oil and gas companies. While several conferences have convened on the topic, this book is the first reliable reference to provide a well-rounded, unbiased approach on the fundamental causes of lost circulation, how to diagnose it in the well, and how to treat and prevent it in future well planning operations. As today’s drilling operations become more complex, and include situations such as sub-salt formations, deepwater wells with losses caused by cooling, and more depleted reservoirs with reduced in-situ stresses, this book provides critical content on the current state of the industry that includes a breakdown of basics on stresses and fractures and how drilling fluids work in the wellbore. The book then covers the more practical issues caused by induced fractures, such as how to understand where the losses are occurring and how to use proven preventative measures such as wellbore strengthening and the effect of base fluid on lost circulation performance. Supported by realistic case studies, this book separates the many myths from the known facts, equipping today’s drilling and cementing engineer with a go-to solution for every day well challenges. Understand the processes, challenges and solutions involved in lost circulation, a critical problem in drilling Gain a balance between fundamental understanding and practical application through real-world case studies Succeed in solving lost circulation in today’s operations such as wells involving casing drilling, deepwater, and managed pressure drilling