Overview
- Describes the use of artificial neural networks and fuzzy sets in petroleum engineering
- Explains data mining in petroleum engineering
- Demonstrates the only data driven reservoir modeling and production engineering technique for unconventional resources – especially shale
- Examines tools for analysis, predictive modeling, and optimization of production from shale in the absence of well-understood and well-defined physics of fluid flow in shale
- Includes supplementary material: sn.pub/extras
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Table of contents (11 chapters)
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Front Matter
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Back Matter
Keywords
About this book
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.
Authors and Affiliations
About the author
Bibliographic Information
Book Title: Shale Analytics
Book Subtitle: Data-Driven Analytics in Unconventional Resources
Authors: Shahab D. Mohaghegh
DOI: https://doi.org/10.1007/978-3-319-48753-3
Publisher: Springer Cham
eBook Packages: Energy, Energy (R0)
Copyright Information: Springer International Publishing AG 2017
Hardcover ISBN: 978-3-319-48751-9Published: 17 February 2017
Softcover ISBN: 978-3-319-84008-6Published: 09 September 2018
eBook ISBN: 978-3-319-48753-3Published: 09 February 2017
Edition Number: 1
Number of Pages: XIV, 287
Number of Illustrations: 8 b/w illustrations, 235 illustrations in colour
Topics: Fossil Fuels (incl. Carbon Capture), Data Mining and Knowledge Discovery, Economic Geology, Mineral Resources, Geotechnical Engineering & Applied Earth Sciences