Data-Driven Reservoir Modeling

Title: Data-Driven Reservoir Modeling
Author: Shahab D. Mohaghegh
ISBN: 1613995601 / 9781613995600
Format: Soft Cover
Pages: 166
Publisher: SPE
Year: 2017
Availability: 45-60 days

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Data-Driven Reservoir Modeling introduces new technology and protocols (intelligent systems) that teach the reader how to apply data analytics to solve real-world, reservoir engineering problems. The book describes how to utilize machine-learning-based algorithmic protocols to reduce large quantities of difficult-to-understand data down to actionable, tractable quantities. Through data manipulation via artificial intelligence, the user learns how to exploit imprecision and uncertainty to achieve tractable, robust, low-cost, effective, actionable solutions to challenges facing upstream technologists in the petroleum industry

Tab Article

Chapter 1 : Introduction
Chapter 2 : Data-Driven Problem Solving
Chapter 3 : Reservoir Modeling
Chapter 4 : Data-Driven Technologies
Chapter 5 : Pitfalls of Using Machine Learning in Reservoir Modeling
Chapter 6 : Fact-Based Reservoir Management 
Chapter 7 : Top-Down Modeling
Chapter 8 : The Spatio-Temporal Database
Chapter 9 : History Matching the Top-Down Model 
Chapter 10 : Post-Modeling Analysis of the Top-Down Model
Chapter 11 : Examples and Case Studies
Chapter 12 : Limitations of Data-Driven Reservoir Modeling
Chapter 13 : The Future of Data-Driven Reservoir Modeling