Shale Analytics

Data-Driven Analytics in Unconventional Resources

  • Shahab D. Mohaghegh

Table of contents

  1. Front Matter
    Pages i-xiv
  2. Shahab D. Mohaghegh
    Pages 1-5
  3. Shahab D. Mohaghegh
    Pages 7-28
  4. Shahab D. Mohaghegh
    Pages 29-81
  5. Shahab D. Mohaghegh
    Pages 83-89
  6. Shahab D. Mohaghegh
    Pages 91-108
  7. Shahab D. Mohaghegh
    Pages 109-125
  8. Shahab D. Mohaghegh
    Pages 127-152
  9. Shahab D. Mohaghegh
    Pages 153-227
  10. Shahab D. Mohaghegh
    Pages 229-249
  11. Shahab D. Mohaghegh
    Pages 251-265
  12. Shahab D. Mohaghegh
    Pages 267-278
  13. Back Matter
    Pages 279-287

About this book

Introduction

This book describes the application of modern information technology to reservoir modeling and well management. Data Driven Analytics in Unconventional Resources looks specifically at reservoir modeling and production management of shale reservoirs, since conventional reservoir 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 absence of well-understood and well-defined physics of fluid flow in shale. Also discussed are important insights into completion practices of production from shale Abundant examples and computer code are given that illustrate the operation of Data-Driven Analytics. The flexibility and power of the technique is demonstrated in numerous real-world situations.

Keywords

Data Mining of Shale Well Information Data-Driven Analytics Hydraulic Fracturing in Shale Production Engineering of Shale Reservoir Engineering of Shale Unconventional Resources

Authors and affiliations

  • Shahab D. Mohaghegh
    • 1
  1. 1.Petroleum & Natural Gas EngineeringWest Virginia UniversityMorgantownUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-48753-3
  • Copyright Information Springer International Publishing AG 2017
  • Publisher Name Springer, Cham
  • eBook Packages Energy
  • Print ISBN 978-3-319-48751-9
  • Online ISBN 978-3-319-48753-3
  • About this book
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