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Artificial Intelligent Approaches in Petroleum Geosciences

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Cover of 'Artificial Intelligent Approaches in Petroleum Geosciences'

Table of Contents

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    Book Overview
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    Chapter 1 Intelligent Data Analysis Techniques—Machine Learning and Data Mining
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    Chapter 2 On Meta-heuristics in Optimization and Data Analysis. Application to Geosciences
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    Chapter 3 Genetic Programming Techniques with Applications in the Oil and Gas Industry
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    Chapter 4 Application of Artificial Neural Networks in Geoscience and Petroleum Industry
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    Chapter 5 On Support Vector Regression to Predict Poisson’s Ratio and Young’s Modulus of Reservoir Rock
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    Chapter 6 Use of Active Learning Method to Determine the Presence and Estimate the Magnitude of Abnormally Pressured Fluid Zones: A Case Study from the Anadarko Basin, Oklahoma
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    Chapter 7 Active Learning Method for Estimating Missing Logs in Hydrocarbon Reservoirs
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    Chapter 8 Improving the Accuracy of Active Learning Method via Noise Injection for Estimating Hydraulic Flow Units: An Example from a Heterogeneous Carbonate Reservoir
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    Chapter 9 Well Log Analysis by Global Optimization-based Interval Inversion Method
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    Chapter 10 Permeability Estimation in Petroleum Reservoir by Meta-heuristics: An Overview
Attention for Chapter 8: Improving the Accuracy of Active Learning Method via Noise Injection for Estimating Hydraulic Flow Units: An Example from a Heterogeneous Carbonate Reservoir
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Citations

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Chapter title
Improving the Accuracy of Active Learning Method via Noise Injection for Estimating Hydraulic Flow Units: An Example from a Heterogeneous Carbonate Reservoir
Chapter number 8
Book title
Artificial Intelligent Approaches in Petroleum Geosciences
Published by
Springer, Cham, January 2015
DOI 10.1007/978-3-319-16531-8_8
Book ISBNs
978-3-31-916530-1, 978-3-31-916531-8
Authors

Fouad Bahrpeyma, Constantin Cranganu, Bahman Golchin, Bahrpeyma, Fouad, Cranganu, Constantin, Golchin, Bahman

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 50%
Researcher 2 50%
Readers by discipline Count As %
Earth and Planetary Sciences 2 50%
Computer Science 1 25%
Energy 1 25%

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