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Quantitative Geosciences: Data Analytics, Geostatistics, Reservoir Characterization and Modeling

Overview of attention for book
Quantitative Geosciences: Data Analytics, Geostatistics, Reservoir Characterization and Modeling
Springer International Publishing

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Introduction
  3. Altmetric Badge
    Chapter 2 Probabilistic Analytics for Geoscience Data
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    Chapter 3 Statistical Analysis of Geoscience Data
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    Chapter 4 Correlation Analysis
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    Chapter 5 Principal Component Analysis
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    Chapter 6 Regression-Based Predictive Analytics
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    Chapter 7 Introduction to Geoscience Data Analytics Using Machine Learning
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    Chapter 8 Multiscale Heterogeneities in Reservoir Geology and Petrophysical Properties
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    Chapter 9 Petrophysical Data Analytics for Reservoir Characterization
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    Chapter 10 Facies and Lithofacies Classifications from Well Logs
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    Chapter 11 Generating Facies Probabilities by Integrating Spatial and Frequency Analyses
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    Chapter 12 Seismic Data Analytics for Reservoir Characterization
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    Chapter 13 Geostatistical Variography for Geospatial Variables
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    Chapter 14 Introduction to Geological and Reservoir Modeling
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    Chapter 15 Constructing 3D Model Framework and Change of Support in Data Mapping
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    Chapter 16 Geostatistical Estimation Methods: Kriging
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    Chapter 17 Stochastic Modeling of Continuous Geospatial or Temporal Properties
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    Chapter 18 Geostatistical Modeling of Facies
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    Chapter 19 Porosity Modeling
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    Chapter 20 Permeability Modeling
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    Chapter 21 Water Saturation Modeling and Rock Typing
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    Chapter 22 Hydrocarbon Volumetrics Estimation
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    Chapter 23 Introduction to Model Upscaling, Validation and History Match
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    Chapter 24 Uncertainty Analysis
Overall attention for this book and its chapters
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2 X users

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137 Mendeley
Summary X
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Title
Quantitative Geosciences: Data Analytics, Geostatistics, Reservoir Characterization and Modeling
Published by
Springer International Publishing, June 2019
DOI 10.1007/978-3-030-17860-4
ISBNs
978-3-03-017859-8, 978-3-03-017860-4
Authors

Ma, Y. Z.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 137 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 137 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 14%
Student > Master 18 13%
Student > Bachelor 16 12%
Researcher 13 9%
Student > Doctoral Student 5 4%
Other 13 9%
Unknown 53 39%
Readers by discipline Count As %
Earth and Planetary Sciences 38 28%
Engineering 22 16%
Environmental Science 7 5%
Computer Science 2 1%
Social Sciences 2 1%
Other 8 6%
Unknown 58 42%

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