Machine Learning and Data Science in the Oil and Gas Industry

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  • Author : Patrick Bangert
  • Publisher : Gulf Professional Publishing
  • Pages : 306 pages
  • ISBN : 0128209143
  • Rating : /5 from reviews
CLICK HERE TO GET THIS BOOK >>>Machine Learning and Data Science in the Oil and Gas Industry

Download or Read online Machine Learning and Data Science in the Oil and Gas Industry full in PDF, ePub and kindle. this book written by Patrick Bangert and published by Gulf Professional Publishing which was released on 04 March 2021 with total page 306 pages. We cannot guarantee that Machine Learning and Data Science in the Oil and Gas Industry book is available in the library, click Get Book button and read full online book in your kindle, tablet, IPAD, PC or mobile whenever and wherever You Like. 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 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 BOOK Machine 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

Machine Learning Guide for Oil and Gas Using Python

Machine Learning Guide for Oil and Gas Using Python
  • Author : Hoss Belyadi,Alireza Haghighat
  • Publisher : Elsevier
  • Release : 27 April 2021
GET THIS BOOK Machine 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

Machine Learning and Data Science in the Power Generation Industry

Machine Learning and Data Science in the Power Generation Industry
  • Author : Patrick Bangert
  • Publisher : Elsevier
  • Release : 14 January 2021
GET THIS BOOK Machine Learning and Data Science in the Power Generation Industry

Machine Learning and Data Science in the Power Generation Industry explores current best practices and quantifies the value-add in developing data-oriented computational programs in the power industry, with a particular focus on thoughtfully chosen real-world case studies. It provides a set of realistic pathways for organizations seeking to develop machine learning methods, with a discussion on data selection and curation as well as organizational implementation in terms of staffing and continuing operationalization. It articulates a body of case study–driven

Handbook of Research on Applied AI for International Business and Marketing Applications

Handbook of Research on Applied AI for International Business and Marketing Applications
  • Author : Christiansen, Bryan,Škrinjarić, Tihana
  • Publisher : IGI Global
  • Release : 25 September 2020
GET THIS BOOK Handbook of Research on Applied AI for International Business and Marketing Applications

Artificial intelligence (AI) describes machines/computers that mimic cognitive functions that humans associate with other human minds, such as learning and problem solving. As businesses have evolved to include more automation of processes, it has become more vital to understand AI and its various applications. Additionally, it is important for workers in the marketing industry to understand how to coincide with and utilize these techniques to enhance and make their work more efficient. The Handbook of Research on Applied AI

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  • Publisher : Springer Nature
  • Release : 19 October 2019
GET THIS BOOK High Performance Computing and Big Data Analysis

This book constitutes revised and selected papers from the Second International Congress on High-Performance Computing and Big Data Analysis, TopHPC 2019, held in Tehran, Iran, in April 2019. The 37 full papers and 2 short papers presented in this volume were carefully reviewed and selected from a total of 103 submissions. The papers in the volume are organized acording to the following topical headings: deep learning; big data analytics; Internet of Things.- data mining, neural network and genetic algorithms; performance issuesand quantum computing.

Big Data Applications in Industry 4 0

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  • Author : P. Kaliraj,T. Devi
  • Publisher : CRC Press
  • Release : 10 February 2022
GET THIS BOOK Big Data Applications in Industry 4 0

Industry 4.0 is the latest technological innovation in manufacturing with the goal to increase productivity in a flexible and efficient manner. Changing the way in which manufacturers operate, this revolutionary transformation is powered by various technology advances including Big Data analytics, Internet of Things (IoT), Artificial Intelligence (AI), and cloud computing. Big Data analytics has been identified as one of the significant components of Industry 4.0, as it provides valuable insights for smart factory management. Big Data and Industry 4.0 have the potential

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  • Publisher : CRC Press
  • Release : 13 June 2018
GET THIS BOOK Extracting Innovations

This book considers the most contemporary innovations propelling the extractive industries forward while also creating new environmental and social challenges. The socio-ecological fabric of innovation in the extractive industries is considered through an integrative approach that brings together engineers, natural scientists, and social scientists—academics and practitioners—giving an empirically grounded and realistic evaluation of the innovations in this sector. It synthesizes a series of questions including: Why have these sectors been historically slow to innovate? What specific strategies can

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 BOOK Machine 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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Recent Trends in Information and Communication Technology
  • Author : Faisal Saeed,Nadhmi Gazem,Srikanta Patnaik,Ali Saleh Saed Balaid,Fathey Mohammed
  • Publisher : Springer
  • Release : 24 May 2017
GET THIS BOOK Recent Trends in Information and Communication Technology

This book presents 94 papers from the 2nd International Conference of Reliable Information and Communication Technology 2017 (IRICT 2017), held in Johor, Malaysia, on April 23–24, 2017. Focusing on the latest ICT innovations for data engineering, the book presents several hot research topics, including advances in big data analysis techniques and applications; mobile networks; applications and usability; reliable communication systems; advances in computer vision, artificial intelligence and soft computing; reliable health informatics and cloud computing environments, e-learning acceptance models, recent trends in knowledge management and

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  • Author : Hoss Belyadi,Ebrahim Fathi,Fatemeh Belyadi
  • Publisher : Gulf Professional Publishing
  • Release : 18 June 2019
GET THIS BOOK Hydraulic Fracturing in Unconventional Reservoirs

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,

Recent Trends in Data Science and Soft Computing

Recent Trends in Data Science and Soft Computing
  • Author : Faisal Saeed,Nadhmi Gazem,Fathey Mohammed,Abdelsalam Busalim
  • Publisher : Springer
  • Release : 08 September 2018
GET THIS BOOK Recent Trends in Data Science and Soft Computing

This book presents the proceedings of the 3rd International Conference of Reliable Information and Communication Technology 2018 (IRICT 2018), which was held in Kuala Lumpur, Malaysia, on July 23–24, 2018. The main theme of the conference was “Data Science, AI and IoT Trends for the Fourth Industrial Revolution.” A total of 158 papers were submitted to the conference, of which 103 were accepted and considered for publication in this book. Several hot research topics are covered, including Advances in Data Science and Big Data Analytics, Artificial

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  • Publisher : Apress
  • Release : 12 December 2014
GET THIS BOOK Data Scientists at Work

Data Scientists at Work is a collection of interviews with sixteen of the world's most influential and innovative data scientists from across the spectrum of this hot new profession. "Data scientist is the sexiest job in the 21st century," according to the Harvard Business Review. By 2018, the United States will experience a shortage of 190,000 skilled data scientists, according to a McKinsey report. Through incisive in-depth interviews, this book mines the what, how, and why of the practice of data science

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  • Publisher : Springer Nature
  • Release : 20 August 2020
GET THIS BOOK Cross Reality and Data Science in Engineering

Today, online technologies are at the core of most fields of engineering and society as a whole . This book discusses the fundamentals, applications and lessons learned in the field of online and remote engineering, virtual instrumentation, and other related technologies like Cross Reality, Data Science & Big Data, Internet of Things & Industrial Internet of Things, Industry 4.0, Cyber Security, and M2M & Smart Objects. Since the first Remote Engineering and Virtual Instrumentation (REV) conference in 2004, the event has focused on the use

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  • Author : Tatiana Antipova
  • Publisher : Springer Nature
  • Release : 17 January 2022
GET THIS BOOK Digital Science

This book gathers selected papers that were submitted to the 2021 International Conference on Digital Science (DSIC 2021) that aims to make available the discussion and the publication of papers on all aspects of single and multidisciplinary research on conference topics. DSIC 2021 was held on October 15–17, 2021. An important characteristic feature of conference is the short publication time and worldwide distribution. Written by respected researchers, the book covers a range of innovative topics related to: digital economics; digital education; digital engineering; digital environmental