Harness Oil and Gas Big Data with Analytics

Harness Oil and Gas Big Data with Analytics
Author: Keith R. Holdaway
Publsiher: John Wiley & Sons
Total Pages: 384
Release: 2014-05-05
ISBN 10: 1118910893
ISBN 13: 9781118910894
Language: EN, FR, DE, ES & NL

Harness Oil and Gas Big Data with Analytics Book Review:

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.

Advances in Subsurface Data Analytics

Advances in Subsurface Data Analytics
Author: Shuvajit Bhattacharya,Haibin Di
Publsiher: Elsevier
Total Pages: 400
Release: 2022-03-01
ISBN 10: 0128223081
ISBN 13: 9780128223086
Language: EN, FR, DE, ES & NL

Advances in Subsurface Data Analytics Book Review:

Advances in Subsurface Data Analytics: Traditional and Physics-Based Machine Learning brings together popular, emerging machine learning algorithms and their applications in subsurface analysis, including geology, geophysics and petrophysics. Each chapter focuses on one machine learning algorithm and includes detailed workflow, applications and case studies. In addition, some of the chapters contain algorithm comparisons to better equip readers with different strategies to implement automated workflows for subsurface analysis. This book will help researchers in academia and professional geoscientists working in the oil and gas industry understand and appreciate the existence of machine learning and deep learning models. In addition, users will learn how to optimize performance and explore applications in the geosciences by bringing together several contributions in a single volume. Covers the fundamentals of simple machine learning and emerging deep learning algorithms written by practitioners in academia and industry Presents detailed case studies of individual machine learning algorithms around the world, including those used for conventional and unconventional reservoirs Offers an analysis of future trends

Harness Oil and Gas Big Data with Analytics

Harness Oil and Gas Big Data with Analytics
Author: Keith R. Holdaway
Publsiher: John Wiley & Sons
Total Pages: 384
Release: 2014-05-27
ISBN 10: 1118779312
ISBN 13: 9781118779316
Language: EN, FR, DE, ES & NL

Harness Oil and Gas Big Data with Analytics Book Review:

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.

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 10: 1119302587
ISBN 13: 9781119302582
Language: EN, FR, DE, ES & NL

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

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.

Quantitative Analysis of Mineral and Energy Resources

Quantitative Analysis of Mineral and Energy Resources
Author: C.F. Chung,Andrea G. Fabbri,R. Sinding-Larsen
Publsiher: Springer Science & Business Media
Total Pages: 738
Release: 2012-12-06
ISBN 10: 9400940297
ISBN 13: 9789400940291
Language: EN, FR, DE, ES & NL

Quantitative Analysis of Mineral and Energy Resources Book Review:

This volume contains the edited papers prepared by lecturers and participants of the NATO Advanced Study Institute on "Statistical Treatments for Estimation of Mineral and Energy Resources" held at II Ciocco (Lucca), Italy, June 22 - July 4, 1986. During the past twenty years, tremendous efforts have been made to acquire quantitative geoscience information from ore deposits, geochemical, geophys ical and remotely-sensed measurements. In October 1981, a two-day symposium on "Quantitative Resource Evaluation" and a three-day workshop on "Interactive Systems for Multivariate Analysis and Image Processing for Resource Evaluation" were held in Ottawa, jointly sponsored by the Geological Survey of Canada, the International Association for Mathematical Geology, and the International Geological Correlation Programme. Thirty scientists from different countries in Europe and North America were invited to form a forum for the discussion of quantitative methods for mineral and energy resource assessment. Since then, not only a multitude of research projects directed toward quantitative analysis in the Earth Sciences, but also recent advances in hardware and software technology, such as high-resolution graphics, data-base management systems and statistical packages on mini and micro-computers, made it possible to study large geoscience data sets. In addition, methods of image analysis have been utilized to capture data in digital form and to supply a variety of tools for charaterizing natural phenomena.

Future Directions for the U S Geological Survey s Energy Resources Program

Future Directions for the U S  Geological Survey s Energy Resources Program
Author: National Academies of Sciences, Engineering, and Medicine,Division on Earth and Life Studies,Board on Earth Sciences and Resources,Committee on Earth Resources,Committee on Future Directions for the U.S. Geological Survey's Energy Resources Program
Publsiher: National Academies Press
Total Pages: 168
Release: 2018-09-04
ISBN 10: 0309477433
ISBN 13: 9780309477437
Language: EN, FR, DE, ES & NL

Future Directions for the U S Geological Survey s Energy Resources Program Book Review:

Reliable, affordable, and technically recoverable energy is central to the nation's economic and social vitality. The United States is both a major consumer of geologically based energy resources from around the world and - increasingly of late - a developer of its own energy resources. Understanding the national and global availability of those resources as well as the environmental impacts of their development is essential for strategic decision making related to the nation's energy mix. The U.S. Geological Survey Energy Resources Program is charged with providing unbiased and publicly available national- and regional-scale assessments of the location, quantity, and quality of geologically based energy resources and with undertaking research related to their development. At the request of the Energy Resources Program (ERP), this publication considers the nation's geologically based energy resource challenges in the context of current national and international energy outlooks. Future Directions for the U.S. Geological Survey's Energy Resources Program examines how ERP activities and products address those challenges and align with the needs federal and nonfederal consumers of ERP products. This study contains recommendations to develop ERP products over the next 10-15 years that will most effectively inform both USGS energy research priorities and the energy needs and priorities of the U.S. government.

Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making

Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making
Author: Cengiz Kahraman,Selcuk Cebi,Sezi Cevik Onar,Basar Oztaysi,A. Cagri Tolga,Irem Ucal Sari
Publsiher: Springer
Total Pages: 1392
Release: 2019-07-05
ISBN 10: 3030237567
ISBN 13: 9783030237561
Language: EN, FR, DE, ES & NL

Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making Book Review:

This book includes the proceedings of the Intelligent and Fuzzy Techniques INFUS 2019 Conference, held in Istanbul, Turkey, on July 23–25, 2019. Big data analytics refers to the strategy of analyzing large volumes of data, or big data, gathered from a wide variety of sources, including social networks, videos, digital images, sensors, and sales transaction records. Big data analytics allows data scientists and various other users to evaluate large volumes of transaction data and other data sources that traditional business systems would be unable to tackle. Data-driven and knowledge-driven approaches and techniques have been widely used in intelligent decision-making, and they are increasingly attracting attention due to their importance and effectiveness in addressing uncertainty and incompleteness. INFUS 2019 focused on intelligent and fuzzy systems with applications in big data analytics and decision-making, providing an international forum that brought together those actively involved in areas of interest to data science and knowledge engineering. These proceeding feature about 150 peer-reviewed papers from countries such as China, Iran, Turkey, Malaysia, India, USA, Spain, France, Poland, Mexico, Bulgaria, Algeria, Pakistan, Australia, Lebanon, and Czech Republic.

Use of Earth Observations for Actionable Decision Making in the Developing World

Use of Earth Observations for Actionable Decision Making in the Developing World
Author: Niall Patrick Hanan,Ashutosh S. Limaye,Daniel Eric Irwin
Publsiher: Frontiers Media SA
Total Pages: 135
Release: 2021-01-13
ISBN 10: 2889663825
ISBN 13: 9782889663828
Language: EN, FR, DE, ES & NL

Use of Earth Observations for Actionable Decision Making in the Developing World Book Review:

National Geothermal Data System

National Geothermal Data System
Author: Anonim
Publsiher: Unknown
Total Pages: 135
Release: 2013
ISBN 10: 1928374650XXX
ISBN 13: OCLC:971473883
Language: EN, FR, DE, ES & NL

National Geothermal Data System Book Review:

Compendium of Papers from the 38th Workshop on Geothermal Reservoir Engineering Stanford University, Stanford, California February 11-13, 2013 The National Geothermal Data System (NGDS) is a distributed, interoperable network of data collected from state geological surveys across all fifty states and the nation's leading academic geothermal centers. The system serves as a platform for sharing consistent, reliable, geothermal-relevant technical data with users of all types, while supplying tools relevant for their work. As aggregated data supports new scientific findings, this content-rich linked data ultimately broadens the pool of knowledge available to promote discovery and development of commercial-scale geothermal energy production. Most of the up-front risks associated with geothermal development stem from exploration and characterization of subsurface resources. Wider access to distributed data will, therefore, result in lower costs for geothermal development. NGDS is on track to become fully operational by 2014 and will provide a platform for custom applications for accessing geothermal relevant data in the U.S. and abroad. It is being built on the U.S. Geoscience Information Network (USGIN) data integration framework to promote interoperability across the Earth sciences community. The basic structure of the NGDS employs state-of-the art informatics to advance geothermal knowledge. The following four papers comprising this Open-File Report are a compendium of presentations, from the 38th Annual Workshop on Geothermal Reservoir Engineering, taking place February 11-13, 2013 at Stanford University, Stanford, California. "NGDS Geothermal Data Domain: Assessment of Geothermal Community Data Needs," outlines the efforts of a set of nationwide data providers to supply data for the NGDS. In particular, data acquisition, delivery, and methodology are discussed. The paper addresses the various types of data and metadata required and why simple links to existing data are insufficient for promoting geothermal exploration. Authors of this paper are Arlene Anderson, US DOE Geothermal Technologies Office, David Blackwell, Southern Methodist University (SMU), Cathy Chickering (SMU), Toni Boyd, Oregon Institute of Technology's GeoHeat Center, Roland Horne, Stanford University, Matthew MacKenzie, Uberity, Joe Moore, University of Utah, Duane Nickull, Uberity, Stephen Richard, Arizona Geological Survey, and Lisa Shevenell, University of Nevada, Reno. "NGDS User Centered Design: Meeting the Needs of the Geothermal Community," discusses the user- centered design approach taken in the development of a user interface solution for the NGDS. The development process is research based, highly collaborative, and incorporates state-of-the-art practices to ensure a quality user interface for the widest and greatest utility. Authors of this paper are Harold Blackman, Boise State University, Suzanne Boyd, Anthro-Tech, Kim Patten, Arizona Geological Survey, and Sam Zheng, Siemens Corporate Research. "Fueling Innovation and Adoption by Sharing Data on the DOE Geothermal Data Repository Node on the National Geothermal Data System," describes the motivation behind the development of the Geothermal Data Repository (GDR) and its role in the NGDS. This includes the benefits of using the GDR to share geothermal data of all types and DOE's data submission process. Authors of this paper are Jon Weers, National Renewable Energy Laboratory and Arlene Anderson, US DOE Geothermal Technologies Office. Finally, "Developing the NGDS Adoption of CKAN for Domestic & International Data Deployment," provides an overview of the "Node-In-A-Box" software package designed to provide data consumers with a highly functional interface to access the system, and to ease the burden on data providers who wish to publish data in the system. It is important to note that this software package constitutes a reference implementation and that the NGDS architecture is based on open sta ...

Proceedings of 3rd International Conference on Computing Informatics and Networks

Proceedings of 3rd International Conference on Computing Informatics and Networks
Author: Ajith Abraham,Oscar Castillo,Deepali Virmani
Publsiher: Springer Nature
Total Pages: 659
Release: 2021-03-14
ISBN 10: 981159712X
ISBN 13: 9789811597121
Language: EN, FR, DE, ES & NL

Proceedings of 3rd International Conference on Computing Informatics and Networks Book Review:

This book is a collection of high-quality peer-reviewed research papers presented in the Third International Conference on Computing Informatics and Networks (ICCIN 2020) organized by the Department of Computer Science and Engineering (CSE), Bhagwan Parshuram Institute of Technology (BPIT), Delhi, India, during 29–30 July 2020. The book discusses a wide variety of industrial, engineering and scientific applications of the emerging techniques. Researchers from academic and industry present their original work and exchange ideas, information, techniques and applications in the field of artificial intelligence, expert systems, software engineering, networking, machine learning, natural language processing and high-performance computing.

Data Analytics for Drilling Engineering

Data Analytics for Drilling Engineering
Author: Qilong Xue
Publsiher: Springer Nature
Total Pages: 312
Release: 2019-12-30
ISBN 10: 303034035X
ISBN 13: 9783030340353
Language: EN, FR, DE, ES & NL

Data Analytics for Drilling Engineering Book Review:

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.

Energy Fact Book

Energy Fact Book
Author: Anonim
Publsiher: Unknown
Total Pages: 135
Release: 1976
ISBN 10: 1928374650XXX
ISBN 13: STANFORD:36105211338129
Language: EN, FR, DE, ES & NL

Energy Fact Book Book Review:

International Energy Outlook

International Energy Outlook
Author: Anonim
Publsiher: Unknown
Total Pages: 135
Release: 1999
ISBN 10: 1928374650XXX
ISBN 13: MINN:31951D02403023K
Language: EN, FR, DE, ES & NL

International Energy Outlook Book Review:

Data Science for Business

Data Science for Business
Author: Foster Provost,Tom Fawcett
Publsiher: "O'Reilly Media, Inc."
Total Pages: 414
Release: 2013-07-27
ISBN 10: 1449374298
ISBN 13: 9781449374297
Language: EN, FR, DE, ES & NL

Data Science for Business Book Review:

Annotation This broad, deep, but not-too-technical guide introduces you to the fundamental principles of data science and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. By learning data science principles, you will understand the many data-mining techniques in use today. More importantly, these principles underpin the processes and strategies necessary to solve business problems through data mining techniques.

Big Data Analytics for Cyber Physical System in Smart City

Big Data Analytics for Cyber Physical System in Smart City
Author: Mohammed Atiquzzaman,Neil Yen,Zheng Xu
Publsiher: Springer Nature
Total Pages: 2016
Release: 2020-01-11
ISBN 10: 9811525684
ISBN 13: 9789811525681
Language: EN, FR, DE, ES & NL

Big Data Analytics for Cyber Physical System in Smart City Book Review:

This book gathers a selection of peer-reviewed papers presented at the first Big Data Analytics for Cyber-Physical System in Smart City (BDCPS 2019) conference, held in Shengyang, China, on 28–29 December 2019. The contributions, prepared by an international team of scientists and engineers, cover the latest advances made in the field of machine learning, and big data analytics methods and approaches for the data-driven co-design of communication, computing, and control for smart cities. Given its scope, it offers a valuable resource for all researchers and professionals interested in big data, smart cities, and cyber-physical systems.

Shale Analytics

Shale Analytics
Author: Shahab D. Mohaghegh
Publsiher: Springer
Total Pages: 287
Release: 2017-02-09
ISBN 10: 3319487531
ISBN 13: 9783319487533
Language: EN, FR, DE, ES & NL

Shale Analytics Book Review:

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.

Big Data Analytics

Big Data Analytics
Author: Soraya Sedkaoui,Mounia Khelfaoui,Nadjat Kadi
Publsiher: CRC Press
Total Pages: 326
Release: 2021-07-05
ISBN 10: 1000290530
ISBN 13: 9781000290530
Language: EN, FR, DE, ES & NL

Big Data Analytics Book Review:

This volume explores the diverse applications of advanced tools and technologies of the emerging field of big data and their evidential value in business. It examines the role of analytics tools and methods of using big data in strengthening businesses to meet today’s information challenges and shows how businesses can adapt big data for effective businesses practices. This volume shows how big data and the use of data analytics is being effectively adopted more frequently, especially in companies that are looking for new methods to develop smarter capabilities and tackle challenges in dynamic processes. Many illustrative case studies are presented that highlight how companies in every sector are now focusing on harnessing data to create a new way of doing business.

Research Anthology on Big Data Analytics Architectures and Applications

Research Anthology on Big Data Analytics  Architectures  and Applications
Author: Management Association, Information Resources
Publsiher: IGI Global
Total Pages: 1988
Release: 2021-09-24
ISBN 10: 1668436639
ISBN 13: 9781668436639
Language: EN, FR, DE, ES & NL

Research Anthology on Big Data Analytics Architectures and Applications Book Review:

Society is now completely driven by data with many industries relying on data to conduct business or basic functions within the organization. With the efficiencies that big data bring to all institutions, data is continuously being collected and analyzed. However, data sets may be too complex for traditional data-processing, and therefore, different strategies must evolve to solve the issue. The field of big data works as a valuable tool for many different industries. The Research Anthology on Big Data Analytics, Architectures, and Applications is a complete reference source on big data analytics that offers the latest, innovative architectures and frameworks and explores a variety of applications within various industries. Offering an international perspective, the applications discussed within this anthology feature global representation. Covering topics such as advertising curricula, driven supply chain, and smart cities, this research anthology is ideal for data scientists, data analysts, computer engineers, software engineers, technologists, government officials, managers, CEOs, professors, graduate students, researchers, and academicians.

Privacy Vulnerabilities and Data Security Challenges in the IoT

Privacy Vulnerabilities and Data Security Challenges in the IoT
Author: Shivani Agarwal,Sandhya Makkar,Duc-Tan Tran
Publsiher: CRC Press
Total Pages: 220
Release: 2020-11-23
ISBN 10: 1000201600
ISBN 13: 9781000201604
Language: EN, FR, DE, ES & NL

Privacy Vulnerabilities and Data Security Challenges in the IoT Book Review:

This book discusses the evolution of security and privacy issues in the Internet of Things (IoT). The book focuses on assembling all security- and privacy-related technologies into a single source so that students, researchers, academics, and those in the industry can easily understand the IoT security and privacy issues. This edited book discusses the use of security engineering and privacy-by-design principles to design a secure IoT ecosystem and to implement cyber-security solutions. This book takes the readers on a journey that begins with understanding security issues in IoT-enabled technologies and how these can be applied in various sectors. It walks readers through engaging with security challenges and building a safe infrastructure for IoT devices. The book helps researchers and practitioners understand the security architecture of IoT and the state-of-the-art in IoT countermeasures. It also differentiates security threats in IoT-enabled infrastructure from traditional ad hoc or infrastructural networks, and provides a comprehensive discussion on the security challenges and solutions in RFID and WSNs in IoT. This book aims to highlight the concepts of related technologies and novel findings by researchers through its chapter organization. The primary audience comprises specialists, researchers, graduate students, designers, experts, and engineers undertaking research on security-related issues.

Recent Advances in Technology Acceptance Models and Theories

Recent Advances in Technology Acceptance Models and Theories
Author: Mostafa Al-Emran,Khaled Shaalan
Publsiher: Springer Nature
Total Pages: 520
Release: 2021-04-16
ISBN 10: 3030649873
ISBN 13: 9783030649876
Language: EN, FR, DE, ES & NL

Recent Advances in Technology Acceptance Models and Theories Book Review:

This book tackles the latest research trends in technology acceptance models and theories. It presents high-quality empirical and review studies focusing on the main theoretical models and their applications across various technologies and contexts. It also provides insights into the theoretical and practical aspects of different technological innovations that assist decision-makers in formulating the required policies and procedures for adopting a specific technology.