Understanding Data Analytics And Predictive Modelling In The Oil And Gas Industry

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Understanding Data Analytics and Predictive Modelling in the Oil and Gas Industry

Kingshuk Srivastava,Thipendra P Singh,Manas Ranjan Pradhan,Vinit Kumar Gunjan
Understanding Data Analytics and Predictive Modelling in the Oil and Gas Industry Book PDF

Author : Kingshuk Srivastava,Thipendra P Singh,Manas Ranjan Pradhan,Vinit Kumar Gunjan
Publisher : CRC Press
Page : 187 pages
File Size : 49,7 Mb
Release : 2023-11-20
Category : Technology & Engineering
ISBN : 9781000995114

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Understanding Data Analytics and Predictive Modelling in the Oil and Gas Industry by Kingshuk Srivastava,Thipendra P Singh,Manas Ranjan Pradhan,Vinit Kumar Gunjan Pdf

This book covers aspects of data science and predictive analytics used in the oil and gas industry by looking into the challenges of data processing and data modelling unique to this industry. It includes upstream management, intelligent/digital wells, value chain integration, crude basket forecasting, and so forth. It further discusses theoretical, methodological, well-established, and validated empirical work dealing with various related topics. Special focus has been given to experimental topics with various case studies. Features: Provides an understanding of the basics of IT technologies applied in the oil and gas sector Includes deep comparison between different artificial intelligence techniques Analyzes different simulators in the oil and gas sector as well as discussion of AI applications Focuses on in-depth experimental and applied topics Details different case studies for upstream and downstream This book is aimed at professionals and graduate students in petroleum engineering, upstream industry, data analytics, and digital transformation process in oil and gas.

Understanding Data Analytics and Predictive Modelling in the Oil and Gas Industry

Kingshuk Srivastava,Thipendra P. Singh,Manas Ranjan Pradhan,Vinit Kumar Gunjan
Understanding Data Analytics and Predictive Modelling in the Oil and Gas Industry Book PDF

Author : Kingshuk Srivastava,Thipendra P. Singh,Manas Ranjan Pradhan,Vinit Kumar Gunjan
Publisher : Unknown
Page : 0 pages
File Size : 55,6 Mb
Release : 2024
Category : Gas industry
ISBN : 1003357873

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Understanding Data Analytics and Predictive Modelling in the Oil and Gas Industry by Kingshuk Srivastava,Thipendra P. Singh,Manas Ranjan Pradhan,Vinit Kumar Gunjan Pdf

This book covers aspects of data science and predictive analytics used in the oil and gas industry by looking into the challenges of data processing and data modelling unique to this industry. It includes upstream management, intelligent/digital wells, value chain integration, crude basket forecasting, and so forth. It further discusses theoretical, methodological, well-established, and validated empirical work dealing with various related topics. Special focus has been given to experimental topics with various case studies. Features: Provides an understanding of the basics of IT technologies applied in the oil and gas sector Includes deep comparison between different artificial intelligence techniques Analyzes different simulators in the oil and gas sector as well as discussion of AI applications Focuses on in-depth experimental and applied topics Details different case studies for upstream and downstream This book is aimed at professionals and graduate students in petroleum engineering, upstream industry, data analytics, and digital transformation process in oil and gas.

Harness Oil and Gas Big Data with Analytics

Keith R. Holdaway
Harness Oil and Gas Big Data with Analytics Book PDF

Author : Keith R. Holdaway
Publisher : John Wiley & Sons
Page : 389 pages
File Size : 40,7 Mb
Release : 2014-05-27
Category : Business & Economics
ISBN : 9781118779316

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Harness Oil and Gas Big Data with Analytics by Keith R. Holdaway Pdf

Use big data analytics to efficiently drive oil and gas exploration and production Harness Oil and Gas Big Data with Analytics provides a complete view of big data and analytics techniques as they are applied to the oil and gas industry. Including a compendium of specific case studies, the book underscores the acute need for optimization in the oil and gas exploration and production stages and shows how data analytics can provide such optimization. This spans exploration, development, production and rejuvenation of oil and gas assets. The book serves as a guide for fully leveraging data, statistical, and quantitative analysis, exploratory and predictive modeling, and fact-based management to drive decision making in oil and gas operations. This comprehensive resource delves into the three major issues that face the oil and gas industry during the exploration and production stages: Data management, including storing massive quantities of data in a manner conducive to analysis and effectively retrieving, backing up, and purging data Quantification of uncertainty, including a look at the statistical and data analytics methods for making predictions and determining the certainty of those predictions Risk assessment, including predictive analysis of the likelihood that known risks are realized and how to properly deal with unknown risks Covering the major issues facing the oil and gas industry in the exploration and production stages, Harness Big Data with Analytics reveals how to model big data to realize efficiencies and business benefits.

Machine Learning and Data Science in the Oil and Gas Industry

Patrick Bangert
Machine Learning and Data Science in the Oil and Gas Industry Book PDF

Author : Patrick Bangert
Publisher : Elsevier
Page : 288 pages
File Size : 44,7 Mb
Release : 2021-03-08
Category : Computers
ISBN : 9780128207147

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Machine Learning and Data Science in the Oil and Gas Industry by Patrick Bangert Pdf

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)

Applied Statistical Modeling and Data Analytics

Srikanta Mishra,Akhil Datta-Gupta
Applied Statistical Modeling and Data Analytics Book PDF

Author : Srikanta Mishra,Akhil Datta-Gupta
Publisher : Elsevier
Page : 250 pages
File Size : 41,8 Mb
Release : 2017-10-27
Category : Science
ISBN : 9780128032800

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Applied Statistical Modeling and Data Analytics by Srikanta Mishra,Akhil Datta-Gupta Pdf

Applied Statistical Modeling and Data Analytics: A Practical Guide for the Petroleum Geosciences provides a practical guide to many of the classical and modern statistical techniques that have become established for oil and gas professionals in recent years. It serves as a "how to" reference volume for the practicing petroleum engineer or geoscientist interested in applying statistical methods in formation evaluation, reservoir characterization, reservoir modeling and management, and uncertainty quantification. Beginning with a foundational discussion of exploratory data analysis, probability distributions and linear regression modeling, the book focuses on fundamentals and practical examples of such key topics as multivariate analysis, uncertainty quantification, data-driven modeling, and experimental design and response surface analysis. Data sets from the petroleum geosciences are extensively used to demonstrate the applicability of these techniques. The book will also be useful for professionals dealing with subsurface flow problems in hydrogeology, geologic carbon sequestration, and nuclear waste disposal. Authored by internationally renowned experts in developing and applying statistical methods for oil & gas and other subsurface problem domains Written by practitioners for practitioners Presents an easy to follow narrative which progresses from simple concepts to more challenging ones Includes online resources with software applications and practical examples for the most relevant and popular statistical methods, using data sets from the petroleum geosciences Addresses the theory and practice of statistical modeling and data analytics from the perspective of petroleum geoscience applications

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

Keith R. Holdaway,Duncan H. B. Irving
Enhance Oil and Gas Exploration with Data Driven Geophysical and Petrophysical Models Book PDF

Author : Keith R. Holdaway,Duncan H. B. Irving
Publisher : John Wiley & Sons
Page : 368 pages
File Size : 41,6 Mb
Release : 2017-10-04
Category : Business & Economics
ISBN : 9781119302582

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Enhance Oil and Gas Exploration with Data-Driven Geophysical and Petrophysical Models by Keith R. Holdaway,Duncan H. B. Irving Pdf

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.

Machine Learning and Data Science in the Oil and Gas Industry

Patrick Bangert
Machine Learning and Data Science in the Oil and Gas Industry Book PDF

Author : Patrick Bangert
Publisher : Gulf Professional Publishing
Page : 290 pages
File Size : 45,9 Mb
Release : 2021-03-04
Category : Science
ISBN : 9780128209141

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Machine Learning and Data Science in the Oil and Gas Industry by Patrick Bangert Pdf

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)

Harness Oil and Gas Big Data with Analytics

Keith R. Holdaway
Harness Oil and Gas Big Data with Analytics Book PDF

Author : Keith R. Holdaway
Publisher : John Wiley & Sons
Page : 389 pages
File Size : 47,9 Mb
Release : 2014-05-05
Category : Business & Economics
ISBN : 9781118910894

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Harness Oil and Gas Big Data with Analytics by Keith R. Holdaway Pdf

Use big data analytics to efficiently drive oil and gas exploration and production Harness Oil and Gas Big Data with Analytics provides a complete view of big data and analytics techniques as they are applied to the oil and gas industry. Including a compendium of specific case studies, the book underscores the acute need for optimization in the oil and gas exploration and production stages and shows how data analytics can provide such optimization. This spans exploration, development, production and rejuvenation of oil and gas assets. The book serves as a guide for fully leveraging data, statistical, and quantitative analysis, exploratory and predictive modeling, and fact-based management to drive decision making in oil and gas operations. This comprehensive resource delves into the three major issues that face the oil and gas industry during the exploration and production stages: Data management, including storing massive quantities of data in a manner conducive to analysis and effectively retrieving, backing up, and purging data Quantification of uncertainty, including a look at the statistical and data analytics methods for making predictions and determining the certainty of those predictions Risk assessment, including predictive analysis of the likelihood that known risks are realized and how to properly deal with unknown risks Covering the major issues facing the oil and gas industry in the exploration and production stages, Harness Big Data with Analytics reveals how to model big data to realize efficiencies and business benefits.

Proceedings of the 2nd International Conference on Emerging Technologies and Intelligent Systems

Mohammed A. Al-Sharafi,Mostafa Al-Emran,Mohammed Naji Al-Kabi,Khaled Shaalan
Proceedings of the 2nd International Conference on Emerging Technologies and Intelligent Systems Book PDF

Author : Mohammed A. Al-Sharafi,Mostafa Al-Emran,Mohammed Naji Al-Kabi,Khaled Shaalan
Publisher : Springer Nature
Page : 703 pages
File Size : 55,8 Mb
Release : 2022-12-12
Category : Technology & Engineering
ISBN : 9783031204296

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Proceedings of the 2nd International Conference on Emerging Technologies and Intelligent Systems by Mohammed A. Al-Sharafi,Mostafa Al-Emran,Mohammed Naji Al-Kabi,Khaled Shaalan Pdf

This book sheds light on the recent research directions in intelligent systems and their applications. It involves four main themes: artificial intelligence and data science, recent trends in software engineering, emerging technologies in education, and intelligent health informatics. The discussion of the most recent designs, advancements, and modifications of intelligent systems, as well as their applications, is a key component of the chapters contributed to the aforementioned subjects.

Shale Analytics

Shahab D. Mohaghegh
Shale Analytics Book PDF

Author : Shahab D. Mohaghegh
Publisher : Springer
Page : 287 pages
File Size : 48,9 Mb
Release : 2017-02-09
Category : Technology & Engineering
ISBN : 9783319487533

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Shale Analytics by Shahab D. Mohaghegh Pdf

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.

Practical Data Science with Hadoop and Spark

Ofer Mendelevitch,Casey Stella,Douglas Eadline
Practical Data Science with Hadoop and Spark Book PDF

Author : Ofer Mendelevitch,Casey Stella,Douglas Eadline
Publisher : Addison-Wesley Professional
Page : 463 pages
File Size : 43,9 Mb
Release : 2016-12-08
Category : Computers
ISBN : 9780134029726

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Practical Data Science with Hadoop and Spark by Ofer Mendelevitch,Casey Stella,Douglas Eadline Pdf

The Complete Guide to Data Science with Hadoop—For Technical Professionals, Businesspeople, and Students Demand is soaring for professionals who can solve real data science problems with Hadoop and Spark. Practical Data Science with Hadoop® and Spark is your complete guide to doing just that. Drawing on immense experience with Hadoop and big data, three leading experts bring together everything you need: high-level concepts, deep-dive techniques, real-world use cases, practical applications, and hands-on tutorials. The authors introduce the essentials of data science and the modern Hadoop ecosystem, explaining how Hadoop and Spark have evolved into an effective platform for solving data science problems at scale. In addition to comprehensive application coverage, the authors also provide useful guidance on the important steps of data ingestion, data munging, and visualization. Once the groundwork is in place, the authors focus on specific applications, including machine learning, predictive modeling for sentiment analysis, clustering for document analysis, anomaly detection, and natural language processing (NLP). This guide provides a strong technical foundation for those who want to do practical data science, and also presents business-driven guidance on how to apply Hadoop and Spark to optimize ROI of data science initiatives. Learn What data science is, how it has evolved, and how to plan a data science career How data volume, variety, and velocity shape data science use cases Hadoop and its ecosystem, including HDFS, MapReduce, YARN, and Spark Data importation with Hive and Spark Data quality, preprocessing, preparation, and modeling Visualization: surfacing insights from huge data sets Machine learning: classification, regression, clustering, and anomaly detection Algorithms and Hadoop tools for predictive modeling Cluster analysis and similarity functions Large-scale anomaly detection NLP: applying data science to human language

Business Analytics

Dr. K. Soundararajan,Dr. Kadhirvel Ramasamy
Business Analytics Book PDF

Author : Dr. K. Soundararajan,Dr. Kadhirvel Ramasamy
Publisher : Thakur Publication Private Limited
Page : 232 pages
File Size : 52,7 Mb
Release : 2022-03-03
Category : Education
ISBN : 9789354804472

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Business Analytics by Dr. K. Soundararajan,Dr. Kadhirvel Ramasamy Pdf

Buy E-Book of Business Analytics Book For MBA 2nd Semester of Anna University, Chennai

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

Keith R. Holdaway,Duncan H. B. Irving
Enhance Oil and Gas Exploration with Data Driven Geophysical and Petrophysical Models Book PDF

Author : Keith R. Holdaway,Duncan H. B. Irving
Publisher : John Wiley & Sons
Page : 368 pages
File Size : 51,6 Mb
Release : 2017-10-09
Category : Business & Economics
ISBN : 9781119215103

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Enhance Oil and Gas Exploration with Data-Driven Geophysical and Petrophysical Models by Keith R. Holdaway,Duncan H. B. Irving Pdf

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.

The Power of Artificial Intelligence for the Next-Generation Oil and Gas Industry

Pethuru R. Chelliah,Venkatraman Jayasankar,Mats Agerstam,B. Sundaravadivazhagan,Robin Cyriac
The Power of Artificial Intelligence for the Next Generation Oil and Gas Industry Book PDF

Author : Pethuru R. Chelliah,Venkatraman Jayasankar,Mats Agerstam,B. Sundaravadivazhagan,Robin Cyriac
Publisher : John Wiley & Sons
Page : 516 pages
File Size : 47,7 Mb
Release : 2023-12-27
Category : Computers
ISBN : 9781119985587

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The Power of Artificial Intelligence for the Next-Generation Oil and Gas Industry by Pethuru R. Chelliah,Venkatraman Jayasankar,Mats Agerstam,B. Sundaravadivazhagan,Robin Cyriac Pdf

The Power of Artificial Intelligence for the Next-Generation Oil and Gas Industry Comprehensive resource describing how operations, outputs, and offerings of the oil and gas industry can improve via advancements in AI The Power of Artificial Intelligence for the Next-Generation Oil and Gas Industry describes the proven and promising digital technologies and tools available to empower the oil and gas industry to be future-ready. It shows how the widely reported limitations of the oil and gas industry are being nullified through the application of breakthrough digital technologies and how the convergence of digital technologies helps create new possibilities and opportunities to take this industry to its next level. The text demonstrates how scores of proven digital technologies, especially in AI, are useful in elegantly fulfilling complicated requirements such as process optimization, automation and orchestration, real-time data analytics, productivity improvement, employee safety, predictive maintenance, yield prediction, and accurate asset management for the oil and gas industry. The text differentiates and delivers sophisticated use cases for the various stakeholders, providing easy-to-understand information to accurately utilize proven technologies towards achieving real and sustainable industry transformation. The Power of Artificial Intelligence for the Next-Generation Oil and Gas Industry includes information on: How various machine and deep learning (ML/DL) algorithms, the prime modules of AI, empower AI systems to deliver on their promises and potential Key use cases of computer vision (CV) and natural language processing (NLP) as they relate to the oil and gas industry Smart leverage of AI, the Industrial Internet of Things (IIoT), cyber physical systems, and 5G communication Event-driven architecture (EDA), microservices architecture (MSA), blockchain for data and device security, and digital twins Clearly expounding how the power of AI and other allied technologies can be meticulously leveraged by the oil and gas industry, The Power of Artificial Intelligence for the Next-Generation Oil and Gas Industry is an essential resource for students, scholars, IT professionals, and business leaders in many different intersecting fields.

Proceedings of the 9th International Conference on Computational Science and Technology

Dae-Ki Kang,Rayner Alfred,Zamhar Iswandono Bin Awang Ismail,Aslina Baharum,Vinesh Thiruchelvam
Proceedings of the 9th International Conference on Computational Science and Technology Book PDF

Author : Dae-Ki Kang,Rayner Alfred,Zamhar Iswandono Bin Awang Ismail,Aslina Baharum,Vinesh Thiruchelvam
Publisher : Springer Nature
Page : 685 pages
File Size : 44,7 Mb
Release : 2023-04-26
Category : Technology & Engineering
ISBN : 9789811984068

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Proceedings of the 9th International Conference on Computational Science and Technology by Dae-Ki Kang,Rayner Alfred,Zamhar Iswandono Bin Awang Ismail,Aslina Baharum,Vinesh Thiruchelvam Pdf

This book gathers the proceedings of the 9th International Conference on Computational Science and Technology (ICCST 2022), held in Johor Bahru, Malaysia, on August 27–28, 2022. The respective contributions offer practitioners and researchers a range of new computational techniques and solutions, identify emerging issues, and outline future research directions, while also showing them how to apply the latest large-scale, high-performance computational methods.