Data Analytics in Reservoir Engineering - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Data Analytics in Reservoir Engineering write by Sathish Sankaran. This book was released on 2020-10-29. Data Analytics in Reservoir Engineering available in PDF, EPUB and Kindle. Data Analytics in Reservoir Engineering describes the relevance of data analytics for the oil and gas industry, with particular emphasis on reservoir engineering.
Shale Analytics
Shale Analytics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Shale Analytics write by Shahab D. Mohaghegh. This book was released on 2017-02-09. Shale Analytics available in PDF, EPUB and Kindle. 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.
Applied Statistical Modeling and Data Analytics
Applied Statistical Modeling and Data Analytics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Applied Statistical Modeling and Data Analytics write by Srikanta Mishra. This book was released on 2017-10-27. Applied Statistical Modeling and Data Analytics available in PDF, EPUB and Kindle. 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
Data-driven Reservoir Modeling
Data-driven Reservoir Modeling - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Data-driven Reservoir Modeling write by Shahab D. Mohaghegh. This book was released on 2017. Data-driven Reservoir Modeling available in PDF, EPUB and Kindle.
Quantitative Geosciences: Data Analytics, Geostatistics, Reservoir Characterization and Modeling
Quantitative Geosciences: Data Analytics, Geostatistics, Reservoir Characterization and Modeling - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Quantitative Geosciences: Data Analytics, Geostatistics, Reservoir Characterization and Modeling write by Y. Z. Ma. This book was released on 2019-07-15. Quantitative Geosciences: Data Analytics, Geostatistics, Reservoir Characterization and Modeling available in PDF, EPUB and Kindle. Earth science is becoming increasingly quantitative in the digital age. Quantification of geoscience and engineering problems underpins many of the applications of big data and artificial intelligence. This book presents quantitative geosciences in three parts. Part 1 presents data analytics using probability, statistical and machine-learning methods. Part 2 covers reservoir characterization using several geoscience disciplines: including geology, geophysics, petrophysics and geostatistics. Part 3 treats reservoir modeling, resource evaluation and uncertainty analysis using integrated geoscience, engineering and geostatistical methods. As the petroleum industry is heading towards operating oil fields digitally, a multidisciplinary skillset is a must for geoscientists who need to use data analytics to resolve inconsistencies in various sources of data, model reservoir properties, evaluate uncertainties, and quantify risk for decision making. This book intends to serve as a bridge for advancing the multidisciplinary integration for digital fields. The goal is to move beyond using quantitative methods individually to an integrated descriptive-quantitative analysis. In big data, everything tells us something, but nothing tells us everything. This book emphasizes the integrated, multidisciplinary solutions for practical problems in resource evaluation and field development.
