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Applications of Artificial Intelligence Techniques in the Petroleum Industry

Applications of Artificial Intelligence Techniques in the Petroleum Industry
  • Author : Abdolhossein Hemmati Sarapardeh
  • Publsiher : Gulf Professional Publishing
  • Release : 26 August 2020
  • ISBN : 0128223855
  • Pages : 322 pages
  • Rating : 4/5 from 21 ratings
GET THIS BOOKApplications of Artificial Intelligence Techniques in the Petroleum Industry

Summary:
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


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
  • Publisher : Gulf Professional Publishing
  • Release : 26 August 2020
GET THIS BOOKApplications of Artificial Intelligence Techniques in the Petroleum Industry

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

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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
  • Publisher : Gulf Professional Publishing
  • Release : 09 September 2020
GET THIS BOOKApplications of Artificial Intelligence Techniques in the Petroleum Industry

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

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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
  • Publisher : Gulf Professional Publishing
  • Release : 04 March 2021
GET THIS BOOKMachine Learning and Data Science in the Oil and Gas Industry

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

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Machine Learning Guide for Oil and Gas Using Python

Machine Learning Guide for Oil and Gas Using Python
  • Author : Hoss Belyadi,Alireza Haghighat
  • Publisher : Gulf Professional Publishing
  • Release : 09 April 2021
GET THIS BOOKMachine Learning Guide for Oil and Gas Using Python

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

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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
  • Publisher : Apress
  • Release : 03 November 2020
GET THIS BOOKMachine Learning in the Oil and Gas Industry

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

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Environmental Issues of Blasting

Environmental Issues of Blasting
  • Author : Ramesh M. Bhatawdekar,Danial Jahed Armaghani,Aydin Azizi
  • Publisher : Springer Nature
  • Release : 22 May 2022
GET THIS BOOKEnvironmental Issues of Blasting

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,

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AI Knowledge Transfer from the University to Society

AI Knowledge Transfer from the University to Society
  • Author : José Guadix Martín,Milica Lilic,Marina Rosales Martínez
  • Publisher : CRC Press
  • Release : 19 January 2022
GET THIS BOOKAI Knowledge Transfer from the University to Society

AI Knowledge Transfer from the University to Society: Applications in High-Impact Sectors brings together examples from the "Innovative Ecosystem with Artificial Intelligence for Andalusia 2025" project at the University of Seville, a series of sub-projects composed of research groups and different institutions or companies that explore the use of Artificial Intelligence in a variety of high-impact sectors to lead innovation and assist in decision-making. Key Features Includes chapters on health and social welfare, transportation, digital economy, energy efficiency and sustainability, agro-industry,

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Design of Intelligent Applications using Machine Learning and Deep Learning Techniques

Design of Intelligent Applications using Machine Learning and Deep Learning Techniques
  • Author : Ramchandra Sharad Mangrulkar,Antonis Michalas,Narendra Shekokar,Meera Narvekar,Pallavi Vijay Chavan
  • Publisher : CRC Press
  • Release : 15 August 2021
GET THIS BOOKDesign of Intelligent Applications using Machine Learning and Deep Learning Techniques

Machine learning (ML) and deep learning (DL) algorithms are invaluable resources for Industry 4.0 and allied areas and are considered as the future of computing. A subfield called neural networks, to recognize and understand patterns in data, helps a machine carry out tasks in a manner similar to humans. The intelligent models developed using ML and DL are effectively designed and are fully investigated – bringing in practical applications in many fields such as health care, agriculture and security. These algorithms can

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Artificial Intelligence for the Internet of Health Things

Artificial Intelligence for the Internet of Health Things
  • Author : K. Shankar,Eswaran Perumal,Deepak Gupta
  • Publisher : CRC Press
  • Release : 10 May 2021
GET THIS BOOKArtificial Intelligence for the Internet of Health Things

This book discusses research in Artificial Intelligence for the Internet of Health Things. It investigates and explores the possible applications of machine learning, deep learning, soft computing, and evolutionary computing techniques in design, implementation, and optimization of challenging healthcare solutions. This book features a wide range of topics such as AI techniques, IoT, cloud, wearables, and secured data transmission. Written for a broad audience, this book will be useful for clinicians, health professionals, engineers, technology developers, IT consultants, researchers, and

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Advanced AI Techniques and Applications in Bioinformatics

Advanced AI Techniques and Applications in Bioinformatics
  • Author : Loveleen Gaur,Arun Solanki,Samuel Fosso Wamba,Noor Zaman Jhanjhi
  • Publisher : CRC Press
  • Release : 18 October 2021
GET THIS BOOKAdvanced AI Techniques and Applications in Bioinformatics

The advanced AI techniques are essential for resolving various problematic aspects emerging in the field of bioinformatics. This book covers the recent approaches in artificial intelligence and machine learning methods and their applications in Genome and Gene editing, cancer drug discovery classification, and the protein folding algorithms among others. Deep learning, which is widely used in image processing, is also applicable in bioinformatics as one of the most popular artificial intelligence approaches. The wide range of applications discussed in this

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Applications of Artificial Intelligence in Business and Finance

Applications of Artificial Intelligence in Business and Finance
  • Author : Vikas Garg,Shalini Aggarwal,Pooja Tiwari,Prasenjit Chatterjee
  • Publisher : CRC Press
  • Release : 23 December 2021
GET THIS BOOKApplications of Artificial Intelligence in Business and Finance

As transactions and other business functions move online and grow more popular every year, the finance and banking industries face increasingly complex data management and identity theft and fraud issues. AI can bring many financial and business functions to the next level, as systems using deep learning technologies are able to analyze patterns and spot suspicious behavior and potential fraud. In this volume, the focus is on the application of artificial intelligence in finance, business, and related areas. The book

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The Essentials of Machine Learning in Finance and Accounting

The Essentials of Machine Learning in Finance and Accounting
  • Author : Mohammad Zoynul Abedin,M. Kabir Hassan,Petr Hajek,Mohammed Mohi Uddin
  • Publisher : Routledge
  • Release : 21 June 2021
GET THIS BOOKThe Essentials of Machine Learning in Finance and Accounting

Th­is book introduces machine learning in finance and illustrates how we can use computational tools in numerical finance in real-world context. ­These computational techniques are particularly useful in financial risk management, corporate bankruptcy prediction, stock price prediction, and portfolio management. ­The book also offers practical and managerial implications of financial and managerial decision support systems and how these systems capture vast amount of financial data. Business risk and uncertainty are two of the toughest challenges in the financial industry.

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Machine Learning in Signal Processing

Machine Learning in Signal Processing
  • Author : Sudeep Tanwar,Anand Nayyar,Rudra Rameshwar
  • Publisher : CRC Press
  • Release : 10 December 2021
GET THIS BOOKMachine Learning in Signal Processing

Machine Learning in Signal Processing: Applications, Challenges, and the Road Ahead offers a comprehensive approach toward research orientation for familiarizing signal processing (SP) concepts to machine learning (ML). ML, as the driving force of the wave of artificial intelligence (AI), provides powerful solutions to many real-world technical and scientific challenges. This book will present the most recent and exciting advances in signal processing for ML. The focus is on understanding the contributions of signal processing and ML, and its aim

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