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: 306
Release: 2021-03-04
ISBN: 0128209143
Category: Computers
Language: EN, FR, DE, ES & NL

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

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 Guide for Oil and Gas Using Python

Machine Learning Guide for Oil and Gas Using Python
Author: Hoss Belyadi,Alireza Haghighat
Publsiher: Gulf Professional Publishing
Total Pages: 476
Release: 2021-04-09
ISBN: 0128219300
Category: Computers
Language: EN, FR, DE, ES & NL

Machine Learning Guide for Oil and Gas Using Python Book Excerpt:

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

Applications of Artificial Intelligence AI and Machine Learning ML in the Petroleum Industry

Applications of Artificial Intelligence  AI  and Machine Learning  ML  in the Petroleum Industry
Author: Manan Shah,Ameya Kshirsagar,Jainam Panchal
Publsiher: CRC Press
Total Pages: 146
Release: 2022-09-02
ISBN: 1000629554
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Applications of Artificial Intelligence AI and Machine Learning ML in the Petroleum Industry 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.

Artificial Intelligence and Data Analytics for Energy Exploration and Production

Artificial Intelligence and Data Analytics for Energy Exploration and Production
Author: Fred Aminzadeh,Cenk Temizel,Yasin Hajizadeh
Publsiher: John Wiley & Sons
Total Pages: 613
Release: 2022-09-21
ISBN: 1119879698
Category: Science
Language: EN, FR, DE, ES & NL

Artificial Intelligence and Data Analytics for Energy Exploration and Production Book Excerpt:

ARTIFICAL INTELLIGENCE AND DATA ANALYTICS FOR ENERGY EXPLORATION AND PRODUCTION This groundbreaking new book is written by some of the foremost authorities on the application of data science and artificial intelligence techniques in exploration and production in the energy industry, covering the most comprehensive and updated new processes, concepts, and practical applications in the field. The book provides an in-depth treatment of the foundations of Artificial Intelligence (AI) Machine Learning, and Data Analytics (DA). It also includes many of AI-DA applications in oil and gas reservoirs exploration, development, and production. The book covers the basic technical details on many tools used in “smart oil fields”. This includes topics such as pattern recognition, neural networks, fuzzy logic, evolutionary computing, expert systems, artificial intelligence machine learning, human-computer interface, natural language processing, data analytics and next-generation visualization. While theoretical details will be kept to the minimum, these topics are introduced from oil and gas applications viewpoints. In this volume, many case histories from the recent applications of intelligent data to a number of different oil and gas problems are highlighted. The applications cover a wide spectrum of practical problems from exploration to drilling and field development to production optimization, artificial lift, and secondary recovery. Also, the authors demonstrate the effectiveness of intelligent data analysis methods in dealing with many oil and gas problems requiring combining machine and human intelligence as well as dealing with linguistic and imprecise data and rules.

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,Škrinjari?, Tihana
Publsiher: IGI Global
Total Pages: 702
Release: 2020-09-25
ISBN: 1799850781
Category: Business & Economics
Language: EN, FR, DE, ES & NL

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

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 for International Business and Marketing Applications is a critical scholarly publication that provides comprehensive research on artificial intelligence applications within the context of international business. Highlighting a wide range of topics such as diversification, risk management, and artificial intelligence, this book is ideal for marketers, business professionals, academicians, practitioners, researchers, and students.

Handbook of Energy Transitions

Handbook of Energy Transitions
Author: Muhammad Asif
Publsiher: CRC Press
Total Pages: 525
Release: 2022-10-14
ISBN: 1000689433
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Handbook of Energy Transitions Book Excerpt:

The global energy scenario is undergoing an unprecedented transition. In the wake of enormous challenges—such as increased population, higher energy demands, increasing greenhouse gas emissions, depleting fossil fuel reserves, volatile energy prices, geopolitical concerns, and energy insecurity issues—the energy sector is experiencing a transition in terms of energy resources and their utilization. This modern transition is historically more dynamic and multidimensional compared to the past considering the vast technological advancements, socioeconomic implications and political responses, and ever-evolving global policies and regulations. Energy insecurity in terms of its critical dimensions—access, affordability, and reliability—remains a major problem hindering the socioeconomic progress in developing countries. The Handbook of Energy Transitions presents a holistic account of the 21st-century energy transition away from fossil fuels. It provides an overview of the unfolding transition in terms of overall dimensions, drivers, trends, barriers, policies, and geopolitics, and then discusses transition in terms of particular resources or technologies, such as renewable energy systems, solar energy, hydropower, hydrogen and fuel cells, electric vehicles, energy storage systems, batteries, digitalization, smart grids, blockchain, and machine learning. It also discusses the present energy transition in terms of broader policy and developmental perspectives. Further, it examines sustainable development, the economics of energy and green growth, and the role of various technologies and initiatives like renewables, nuclear power, and electrification in promoting energy security and energy transition worldwide. Key Features Includes technical, economic, social, and policy perspectives of energy transitions Features practical case studies and comparative assessments Examines the latest renewable energy and low-carbon technologies Explains the connection between energy transition and global climate change

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: 012804747X
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Intelligent Digital Oil and Gas Fields Book Excerpt:

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 Applications in Subsurface Energy Resource Management

Machine Learning Applications in Subsurface Energy Resource Management
Author: Srikanta Mishra
Publsiher: CRC Press
Total Pages: 388
Release: 2022-12-27
ISBN: 100082389X
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Machine Learning Applications in Subsurface Energy Resource Management Book Excerpt:

The utilization of machine learning (ML) techniques to understand hidden patterns and build data-driven predictive models from complex multivariate datasets is rapidly increasing in many applied science and engineering disciplines, including geo-energy. Motivated by these developments, Machine Learning Applications in Subsurface Energy Resource Management presents a current snapshot of the state of the art and future outlook for ML applications to manage subsurface energy resources (e.g., oil and gas, geologic carbon sequestration, and geothermal energy). Covers ML applications across multiple application domains (reservoir characterization, drilling, production, reservoir modeling, and predictive maintenance) Offers a variety of perspectives from authors representing operating companies, universities, and research organizations Provides an array of case studies illustrating the latest applications of several ML techniques Includes a literature review and future outlook for each application domain This book is targeted at practicing petroleum engineers or geoscientists interested in developing a broad understanding of ML applications across several subsurface domains. It is also aimed as a supplementary reading for graduate-level courses and will also appeal to professionals and researchers working with hydrogeology and nuclear waste disposal.

Emerging Technologies for Sustainable and Smart Energy

Emerging Technologies for Sustainable and Smart Energy
Author: Anirbid Sircar,Gautami Tripathi,Namrata Bist,Kashish Ara Shakil,Mithileysh Sathiyanarayanan
Publsiher: CRC Press
Total Pages: 280
Release: 2022-08-03
ISBN: 1000623610
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Emerging Technologies for Sustainable and Smart Energy Book Excerpt:

Considering the alarming issue of global climate change and its drastic consequences, there is an urgent need to further develop smart and innovative solutions for the energy sector. The goal of sustainable and smart energy for present and future generations can be achieved by integrating emerging technologies into the existing energy infrastructure. This book focuses on the role and significance of emerging technologies in the energy sector and covers the various technological interventions for both conventional and unconventional energy resources and provides meaningful insights into smart and sustainable energy solutions. The book also discusses future directions for smart and sustainable developments in the energy sector.

High Performance Computing and Big Data Analysis

High Performance Computing and Big Data Analysis
Author: Lucio Grandinetti,Seyedeh Leili Mirtaheri,Reza Shahbazian
Publsiher: Springer Nature
Total Pages: 514
Release: 2019-10-19
ISBN: 3030334953
Category: Computers
Language: EN, FR, DE, ES & NL

High Performance Computing and Big Data Analysis Book Excerpt:

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.

Extracting Innovations

Extracting Innovations
Author: Martin J. Clifford,Robert K. Perrons,Saleem H. Ali,Tim A. Grice
Publsiher: CRC Press
Total Pages: 303
Release: 2018-06-13
ISBN: 1351582631
Category: Science
Language: EN, FR, DE, ES & NL

Extracting Innovations Book Excerpt:

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:

Application of Big Data in Petroleum Streams

Application of Big Data in Petroleum Streams
Author: Jay Gohil,Manan Shah
Publsiher: CRC Press
Total Pages: 171
Release: 2022-05-09
ISBN: 1000580024
Category: Computers
Language: EN, FR, DE, ES & NL

Application of Big Data in Petroleum Streams Book Excerpt:

The book aims to provide comprehensive knowledge and information pertaining to application or implementation of big data in the petroleum industry and its operations (such as exploration, production, refining and finance). The book covers intricate aspects of big data such as 6Vs, benefits, applications, implementation, research work and real-world implementation pertaining to each petroleum-associated operation in a concise manner that aids the reader to apprehend the overview of big data’s role in the industry. The book resonates with readers who wish to understand the intricate details of working with big data (along with data science, machine learning and artificial intelligence) in general and how it affects and impacts an entire industry. As the book builds various concepts of big data from scratch to industry level, readers who wish to gain big data-associated knowledge of industry level in simple language from the very fundamentals would find this a wonderful read.

Data Science and Intelligent Systems

Data Science and Intelligent Systems
Author: Radek Silhavy,Petr Silhavy,Zdenka Prokopova
Publsiher: Springer Nature
Total Pages: 1056
Release: 2021-11-16
ISBN: 3030903214
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Data Science and Intelligent Systems Book Excerpt:

This book constitutes the second part of refereed proceedings of the 5th Computational Methods in Systems and Software 2021 (CoMeSySo 2021) proceedings. The real-world problems related to data science and algorithm design related to systems and software engineering are presented in this papers. Furthermore, the basic research’ papers that describe novel approaches in the data science, algorithm design and in systems and software engineering are included. The CoMeSySo 2021 conference is breaking the barriers, being held online. CoMeSySo 2021 intends to provide an international forum for the discussion of the latest high-quality research results

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: 0128223855
Category: Science
Language: EN, FR, DE, ES & NL

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

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

Advances in Subsurface Data Analytics

Advances in Subsurface Data Analytics
Author: Shuvajit Bhattacharya,Haibin Di
Publsiher: Elsevier
Total Pages: 378
Release: 2022-05-18
ISBN: 0128223081
Category: Computers
Language: EN, FR, DE, ES & NL

Advances in Subsurface Data Analytics Book Excerpt:

Advances in Subsurface Data Analytics: Traditional and Physics-Based Approaches brings together the fundamentals of popular and emerging machine learning (ML) algorithms with their applications in subsurface analysis, including geology, geophysics, petrophysics, and reservoir engineering. The book is divided into four parts: traditional ML, deep learning, physics-based ML, and new directions, with an increasing level of diversity and complexity of topics. Each chapter focuses on one ML algorithm with a detailed workflow for a specific application in geosciences. Some chapters also compare the results from an algorithm with others to better equip the readers with different strategies to implement automated workflows for subsurface analysis. Advances in Subsurface Data Analytics: Traditional and Physics-Based Approaches will help researchers in academia and professional geoscientists working on the subsurface-related problems (oil and gas, geothermal, carbon sequestration, and seismology) at different scales to understand and appreciate current trends in ML approaches, their applications, advances and limitations, and future potential in geosciences by bringing together several contributions in a single volume. Covers fundamentals of simple machine learning and deep learning algorithms, and physics-based approaches written by practitioners in academia and industry Presents detailed case studies of individual machine learning algorithms and optimal strategies in subsurface characterization around the world Offers an analysis of future trends in machine learning in geosciences

Enhance Oil and Gas Exploration with Data Driven Geophysical and Petrophysical Models

Enhance Oil and Gas Exploration with Data Driven Geophysical and Petrophysical Models
Author: Keith R. Holdaway,Duncan H. B. Irving
Publsiher: John Wiley & Sons
Total Pages: 368
Release: 2017-10-04
ISBN: 1119302587
Category: Business & Economics
Language: EN, FR, DE, ES & NL

Enhance Oil and Gas Exploration with Data Driven Geophysical and Petrophysical Models Book Excerpt:

Leverage Big Data analytics methodologies to add value to geophysical and petrophysical exploration data Enhance Oil & Gas Exploration with Data-Driven Geophysical and Petrophysical Models demonstrates a new approach to geophysics and petrophysics data analysis using the latest methods drawn from Big Data. Written by two geophysicists with a combined 30 years in the industry, this book shows you how to leverage continually maturing computational intelligence to gain deeper insight from specific exploration data. Case studies illustrate the value propositions of this alternative analytical workflow, and in-depth discussion addresses the many Big Data issues in geophysics and petrophysics. From data collection and context through real-world everyday applications, this book provides an essential resource for anyone involved in oil and gas exploration. Recent and continual advances in machine learning are driving a rapid increase in empirical modeling capabilities. This book shows you how these new tools and methodologies can enhance geophysical and petrophysical data analysis, increasing the value of your exploration data. Apply data-driven modeling concepts in a geophysical and petrophysical context Learn how to get more information out of models and simulations Add value to everyday tasks with the appropriate Big Data application Adjust methodology to suit diverse geophysical and petrophysical contexts Data-driven modeling focuses on analyzing the total data within a system, with the goal of uncovering connections between input and output without definitive knowledge of the system's physical behavior. This multi-faceted approach pushes the boundaries of conventional modeling, and brings diverse fields of study together to apply new information and technology in new and more valuable ways. Enhance Oil & Gas Exploration with Data-Driven Geophysical and Petrophysical Models takes you beyond traditional deterministic interpretation to the future of exploration data analysis.

Application of Big Data Deep Learning Machine Learning and Other Advanced Analytical Techniques in Environmental Economics and Policy

Application of Big Data  Deep Learning  Machine Learning  and Other Advanced Analytical Techniques in Environmental Economics and Policy
Author: Tsun Se Cheong,Xunpeng (Roc) Shi,Yanfei Li,Yongping Sun
Publsiher: Frontiers Media SA
Total Pages: 485
Release: 2022-07-25
ISBN: 2889765962
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Application of Big Data Deep Learning Machine Learning and Other Advanced Analytical Techniques in Environmental Economics and Policy Book Excerpt:

Data Analytics for Drilling Engineering

Data Analytics for Drilling Engineering
Author: Qilong Xue
Publsiher: Springer Nature
Total Pages: 312
Release: 2019-12-30
ISBN: 303034035X
Category: Science
Language: EN, FR, DE, ES & NL

Data Analytics for Drilling Engineering Book Excerpt:

This book presents the signal processing and data mining challenges encountered in drilling engineering, and describes the methods used to overcome them. In drilling engineering, many signal processing technologies are required to solve practical problems, such as downhole information transmission, spatial attitude of drillstring, drillstring dynamics, seismic activity while drilling, among others. This title attempts to bridge the gap between the signal processing and data mining and oil and gas drilling engineering communities. There is an urgent need to summarize signal processing and data mining issues in drilling engineering so that practitioners in these fields can understand each other in order to enhance oil and gas drilling functions. In summary, this book shows the importance of signal processing and data mining to researchers and professional drilling engineers and open up a new area of application for signal processing and data mining scientists.

Quantitative Analysis of Geopressure for Geoscientists and Engineers

Quantitative Analysis of Geopressure for Geoscientists and Engineers
Author: Nader C. Dutta,Ran Bachrach,Tapan Mukerji
Publsiher: Cambridge University Press
Total Pages: 135
Release: 2021-02-28
ISBN: 1009031228
Category: Technology & Engineering
Language: EN, FR, DE, ES & NL

Quantitative Analysis of Geopressure for Geoscientists and Engineers Book Excerpt:

Geopressure, or excess pore pressure in subsurface rock formations that is higher than the hydrostatic pressure, is a worldwide phenomenon which impacts hydrocarbon resource estimation, drilling and drilling safety in operations. This book provides a comprehensive overview of geopressure analysis bringing together rock physics, seismic technology, quantitative basin modeling and geomechanics. It provides a fundamental physical and geological basis for understanding geopressure by explaining the coupled mechanical and thermal processes. It also brings together state-of-the-art tools and technologies for analysis and detection of geopressure, along with the associated uncertainty. Prediction and detection of shallow geohazards and gas hydrates is also discussed and field examples are used to illustrate how models can be practically applied. With supplementary MATLAB® codes and exercises available online, this is an ideal resource for students, researchers and industry professionals in geoscience and petroleum engineering looking to understand and analyse subsurface formation pressure.

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: 2020-09-09
ISBN: 0128186801
Category: Science
Language: EN, FR, DE, ES & NL

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

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