Advances in Subsurface Data Analytics Book

Advances in Subsurface Data Analytics


  • Author : Shuvajit Bhattacharya
  • Publisher : Elsevier
  • Release Date : 2022-05-18
  • Genre: Computers
  • Pages : 378
  • ISBN 10 : 9780128223086
  • Total Read : 80
  • File Size : 12,5 Mb

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Advances in Subsurface Data Analytics Summary:

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

Artificial Intelligence and Data Analytics for Energy Exploration and Production Book

Artificial Intelligence and Data Analytics for Energy Exploration and Production


  • Author : Fred Aminzadeh
  • Publisher : John Wiley & Sons
  • Release Date : 2022-09-21
  • Genre: Science
  • Pages : 613
  • ISBN 10 : 9781119879695
  • Total Read : 99
  • File Size : 5,8 Mb

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Artificial Intelligence and Data Analytics for Energy Exploration and Production Summary:

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.

Harness Oil and Gas Big Data with Analytics Book

Harness Oil and Gas Big Data with Analytics


  • Author : Keith R. Holdaway
  • Publisher : John Wiley & Sons
  • Release Date : 2014-05-05
  • Genre: Business & Economics
  • Pages : 384
  • ISBN 10 : 9781118910894
  • Total Read : 96
  • File Size : 10,6 Mb

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Harness Oil and Gas Big Data with Analytics Summary:

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.

Big Data Analysis  New Algorithms for a New Society Book

Big Data Analysis New Algorithms for a New Society


  • Author : Nathalie Japkowicz
  • Publisher : Springer
  • Release Date : 2015-12-16
  • Genre: Technology & Engineering
  • Pages : 329
  • ISBN 10 : 9783319269894
  • Total Read : 68
  • File Size : 9,5 Mb

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Big Data Analysis New Algorithms for a New Society Summary:

This edited volume is devoted to Big Data Analysis from a Machine Learning standpoint as presented by some of the most eminent researchers in this area. It demonstrates that Big Data Analysis opens up new research problems which were either never considered before, or were only considered within a limited range. In addition to providing methodological discussions on the principles of mining Big Data and the difference between traditional statistical data analysis and newer computing frameworks, this book presents recently developed algorithms affecting such areas as business, financial forecasting, human mobility, the Internet of Things, information networks, bioinformatics, medical systems and life science. It explores, through a number of specific examples, how the study of Big Data Analysis has evolved and how it has started and will most likely continue to affect society. While the benefits brought upon by Big Data Analysis are underlined, the book also discusses some of the warnings that have been issued concerning the potential dangers of Big Data Analysis along with its pitfalls and challenges.

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

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


  • Author : National Academies of Sciences, Engineering, and Medicine
  • Publisher : National Academies Press
  • Release Date : 2018-09-04
  • Genre: Science
  • Pages : 168
  • ISBN 10 : 9780309477437
  • Total Read : 79
  • File Size : 7,9 Mb

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

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.

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

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


  • Author : Keith R. Holdaway
  • Publisher : John Wiley & Sons
  • Release Date : 2017-10-04
  • Genre: Business & Economics
  • Pages : 368
  • ISBN 10 : 9781119302582
  • Total Read : 77
  • File Size : 8,9 Mb

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

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 analy

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

Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making


  • Author : Cengiz Kahraman
  • Publisher : Springer
  • Release Date : 2019-07-05
  • Genre: Technology & Engineering
  • Pages : 1392
  • ISBN 10 : 9783030237561
  • Total Read : 74
  • File Size : 9,6 Mb

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Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making Summary:

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.