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Applications Of Artificial Intelligence Techniques In The Petroleum Industry

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Applications of Artificial Intelligence Techniques in the Petroleum Industry

Applications of Artificial Intelligence Techniques in the Petroleum Industry Book
Author : Abdolhossein Hemmati Sarapardeh,Aydin Larestani,Nait Amar Menad,Sassan Hajirezaie
Publisher : Gulf Professional Publishing
Release : 2020-08-26
ISBN : 0128223855
Language : En, Es, Fr & De

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Book Description :

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

Machine Learning Guide for Oil and Gas Using Python

Machine Learning Guide for Oil and Gas Using Python Book
Author : Hoss Belyadi,Alireza Haghighat
Publisher : Gulf Professional Publishing
Release : 2021-04-09
ISBN : 0128219300
Language : En, Es, Fr & De

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Book Description :

Machine Learning Guide for Oil and Gas Using Python: A Step-by-Step Breakdown with Data, Algorithms, Codes, and Applications delivers a critical training and resource tool to help engineers understand machine learning theory and practice, specifically referencing use cases in oil and gas. The reference moves from explaining how Python works to step-by-step examples of utilization in various oil and gas scenarios, such as well testing, shale reservoirs and production optimization. Petroleum engineers are quickly applying machine learning techniques to their data challenges, but there is a lack of references beyond the math or heavy theory of machine learning. Machine Learning Guide for Oil and Gas Using Python details the open-source tool Python by explaining how it works at an introductory level then bridging into how to apply the algorithms into different oil and gas scenarios. While similar resources are often too mathematical, this book balances theory with applications, including use cases that help solve different oil and gas data challenges. Helps readers understand how open-source Python can be utilized in practical oil and gas challenges Covers the most commonly used algorithms for both supervised and unsupervised learning Presents a balanced approach of both theory and practicality while progressing from introductory to advanced analytical techniques

Machine Learning and Data Science in the Oil and Gas Industry

Machine Learning and Data Science in the Oil and Gas Industry Book
Author : Patrick Bangert
Publisher : Gulf Professional Publishing
Release : 2021-03-04
ISBN : 0128209143
Language : En, Es, Fr & De

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Book Description :

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)

Machine Learning in the Oil and Gas Industry

Machine Learning in the Oil and Gas Industry Book
Author : Yogendra Narayan Pandey,Ayush Rastogi,Sribharath Kainkaryam,Srimoyee Bhattacharya,Luigi Saputelli
Publisher : Apress
Release : 2020-11-03
ISBN : 9781484260937
Language : En, Es, Fr & De

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Book Description :

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.

Data Mining

Data Mining Book
Author : Georg Zangl
Publisher : Unknown
Release : 2003
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Download Data Mining book written by Georg Zangl, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Reservoir Simulations

Reservoir Simulations Book
Author : Shuyu Sun,Tao Zhang
Publisher : Gulf Professional Publishing
Release : 2020-06-18
ISBN : 0128209623
Language : En, Es, Fr & De

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Book Description :

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.

Artificial Intelligence in the Petroleum Industry

Artificial Intelligence in the Petroleum Industry Book
Author : Bertrand Braunschweig,Ron Day
Publisher : Editions TECHNIP
Release : 1995
ISBN : 9782710806882
Language : En, Es, Fr & De

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Book Description :

Download Artificial Intelligence in the Petroleum Industry book written by Bertrand Braunschweig,Ron Day, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Environmental Issues of Blasting

Environmental Issues of Blasting Book
Author : Ramesh M. Bhatawdekar,Danial Jahed Armaghani,Aydin Azizi
Publisher : Springer Nature
Release : 2021
ISBN : 9811682372
Language : En, Es, Fr & De

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Book Description :

This book gives a rigorous and up-to-date study of the various AI and machine learning algorithms for resolving environmental challenges associated with blasting. Blasting is a critical activity in any mining or civil engineering project for breaking down hard rock masses. A small amount of explosive energy is only used during blasting to fracture rock in order to achieve the appropriate fragmentation, throw, and development of muck pile. The surplus energy is transformed into unfavourable environmental effects such as back-break, flyrock, air overpressure, and ground vibration. The advancement of artificial intelligence and machine learning techniques has increased the accuracy of predicting these environmental impacts of blasting. This book discusses the effective application of these strategies in forecasting, mitigating, and regulating the aforementioned blasting environmental hazards.

Intelligent Digital Oil and Gas Fields

Intelligent Digital Oil and Gas Fields Book
Author : Gustavo Carvajal,Marko Maucec,Stan Cullick
Publisher : Gulf Professional Publishing
Release : 2017-12-14
ISBN : 012804747X
Language : En, Es, Fr & De

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Book Description :

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

AI and Learning Systems

AI and Learning Systems Book
Author : Konstantinos Kyprianidis,Erik Dahlquist
Publisher : BoD – Books on Demand
Release : 2021-02-17
ISBN : 1789858771
Language : En, Es, Fr & De

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Book Description :

Over the last few years, interest in the industrial applications of AI and learning systems has surged. This book covers the recent developments and provides a broad perspective of the key challenges that characterize the field of Industry 4.0 with a focus on applications of AI. The target audience for this book includes engineers involved in automation system design, operational planning, and decision support. Computer science practitioners and industrial automation platform developers will also benefit from the timely and accurate information provided in this work. The book is organized into two main sections comprising 12 chapters overall: •Digital Platforms and Learning Systems •Industrial Applications of AI

Evolving Role of AI and IoMT in the Healthcare Market

Evolving Role of AI and IoMT in the Healthcare Market Book
Author : Fadi Al-Turjman,Manoj Kumar,Thompson Stephan,Akashdeep Bhardwaj
Publisher : Springer Nature
Release : 2021
ISBN : 3030820793
Language : En, Es, Fr & De

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Book Description :

This book is a proficient guide to understanding artificial intelligence (IoT) and the Internet of Medical Things (IoMT) in healthcare. The book provides a comprehensive study on the applications of AI and IoT in various medical domains. The book shows how the implementation of innovative solutions in healthcare is beneficial, and IoT, together with AI, are strong drivers of the digital transformation regardless of what field the technologies are applied in. Therefore, this book provides a high level of understanding with the emerging technologies on the Internet of Things, wearable devices, and AI in IoMT, which offers the potential to acquire and process a tremendous amount of data from the physical world. Covers the applications of artificial intelligence (AI), and Internet of Medical Things (IoMT) in the Healthcare domain; Discusses how the usage of IoT and AI helps to analyze medical data in terms of diagnosis, disease prediction, and analysis of enormous health records; Covers a variety of Medical IoT based applications that are being used in different sectors and have succeeded in providing considerable benefits to the users in critical health application.

Industrial Applications of Machine Learning

Industrial Applications of Machine Learning Book
Author : Pedro Larrañaga,David Atienza,Javier Diaz-Rozo,Alberto Ogbechie,Carlos Esteban Puerto-Santana,Concha Bielza
Publisher : CRC Press
Release : 2018-12-12
ISBN : 135112837X
Language : En, Es, Fr & De

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Book Description :

Industrial Applications of Machine Learning shows how machine learning can be applied to address real-world problems in the fourth industrial revolution, and provides the required knowledge and tools to empower readers to build their own solutions based on theory and practice. The book introduces the fourth industrial revolution and its current impact on organizations and society. It explores machine learning fundamentals, and includes four case studies that address a real-world problem in the manufacturing or logistics domains, and approaches machine learning solutions from an application-oriented point of view. The book should be of special interest to researchers interested in real-world industrial problems. Features Describes the opportunities, challenges, issues, and trends offered by the fourth industrial revolution Provides a user-friendly introduction to machine learning with examples of cutting-edge applications in different industrial sectors Includes four case studies addressing real-world industrial problems solved with machine learning techniques A dedicated website for the book contains the datasets of the case studies for the reader's reproduction, enabling the groundwork for future problem-solving Uses of three of the most widespread software and programming languages within the engineering and data science communities, namely R, Python, and Weka

Applications of Machine Learning

Applications of Machine Learning Book
Author : Prashant Johri,Jitendra Kumar Verma,Sudip Paul
Publisher : Springer Nature
Release : 2020-05-04
ISBN : 9811533571
Language : En, Es, Fr & De

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Book Description :

This book covers applications of machine learning in artificial intelligence. The specific topics covered include human language, heterogeneous and streaming data, unmanned systems, neural information processing, marketing and the social sciences, bioinformatics and robotics, etc. It also provides a broad range of techniques that can be successfully applied and adopted in different areas. Accordingly, the book offers an interesting and insightful read for scholars in the areas of computer vision, speech recognition, healthcare, business, marketing, and bioinformatics.

Advanced Analytics and Artificial Intelligence Applications

Advanced Analytics and Artificial Intelligence Applications Book
Author : Ali Soofastaei
Publisher : BoD – Books on Demand
Release : 2019-11-13
ISBN : 1789846382
Language : En, Es, Fr & De

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Book Description :

Computers and machines were developed to reduce time consumption and manual human efforts to complete projects efficiently. With fast-growing technologies in the field, we have finally reached a stage where almost everyone in the world has access to these high technologies. However, this is just a starting phase because future development is taking a more advanced route in the shape of artificial intelligence (AI). Although AI is under the computer science umbrella, nowadays there is no field unaffected by this high technology. The overall aim of using intelligence learning methods is to train machines to think intelligently and make decisions in different situations the same as humans. Previously, machines were doing what they were programmed to do, but now with AI, devices can think and behave like a human being. This book aims to present the application of advanced analytics and AI in different industries as practical tools to develop prediction, optimization, and make decision models.

Artificial Intelligence in Chemical Engineering

Artificial Intelligence in Chemical Engineering Book
Author : Thomas E. Quantrille,Y. A. Liu
Publisher : Elsevier
Release : 2012-12-02
ISBN : 0080571212
Language : En, Es, Fr & De

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Book Description :

Artificial intelligence (AI) is the part of computer science concerned with designing intelligent computer systems (systems that exhibit characteristics we associate with intelligence in human behavior). This book is the first published textbook of AI in chemical engineering, and provides broad and in-depth coverage of AI programming, AI principles, expert systems, and neural networks in chemical engineering. This book introduces the computational means and methodologies that are used to enable computers to perform intelligent engineering tasks. A key goal is to move beyond the principles of AI into its applications in chemical engineering. After reading this book, a chemical engineer will have a firm grounding in AI, know what chemical engineering applications of AI exist today, and understand the current challenges facing AI in engineering. Allows the reader to learn AI quickly using inexpensive personal computers Contains a large number of illustrative examples, simple exercises, and complex practice problems and solutions Includes a computer diskette for an illustrated case study Demonstrates an expert system for separation synthesis (EXSEP) Presents a detailed review of published literature on expert systems and neural networks in chemical engineering

Decision Intelligence Analytics and the Implementation of Strategic Business Management

Decision Intelligence Analytics and the Implementation of Strategic Business Management Book
Author : P. Mary Jeyanthi
Publisher : Springer Nature
Release : 2022-07-05
ISBN : 3030827631
Language : En, Es, Fr & De

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Book Description :

Download Decision Intelligence Analytics and the Implementation of Strategic Business Management book written by P. Mary Jeyanthi, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Artificial Intelligence in the Petroleum Industry

Artificial Intelligence in the Petroleum Industry Book
Author : Bertrand Braunschweig
Publisher : Editions TECHNIP
Release : 1996
ISBN : 9782710807032
Language : En, Es, Fr & De

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Book Description :

Download Artificial Intelligence in the Petroleum Industry book written by Bertrand Braunschweig, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Soft Computing Applications in Industry

Soft Computing Applications in Industry Book
Author : Bhanu Prasad
Publisher : Springer
Release : 2008-02-13
ISBN : 3540774653
Language : En, Es, Fr & De

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Book Description :

Softcomputing techniques play a vital role in the industry. This book presents several important papers presented by some of the well-known scientists from all over the globe. The main techniques of soft computing presented include ant-colony optimization, artificial immune systems, artificial neural networks, Bayesian models. The book includes various examples and application domains such as bioinformatics, detection of phishing attacks, and fault detection of motors.

Mathematical Modeling Computational Intelligence Techniques and Renewable Energy

Mathematical Modeling  Computational Intelligence Techniques and Renewable Energy Book
Author : Manoj Sahni,José M. Merigó,Ritu Sahni,Rajkumar Verma
Publisher : Springer Nature
Release : 2021-12-11
ISBN : 9811659524
Language : En, Es, Fr & De

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Book Description :

This book presents new knowledge and recent developments in all aspects of computational techniques, mathematical modeling, energy systems, and applications of fuzzy sets and intelligent computing. The book is a collection of best selected research papers presented at the Second International Conference on “Mathematical Modeling, Computational Intelligence Techniques and Renewable Energy (MMCITRE 2021),” organized by the Department of Mathematics, Pandit Deendayal Petroleum University, in association with Forum for Interdisciplinary Mathematics. The book provides innovative works of researchers, academicians, and students in the area of interdisciplinary mathematics, statistics, computational intelligence, and renewable energy.

Shale Analytics

Shale Analytics Book
Author : Shahab D. Mohaghegh
Publisher : Springer
Release : 2017-02-09
ISBN : 3319487531
Language : En, Es, Fr & De

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Book Description :

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.