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The Resource Geostatistical reservoir modeling, Michael J. Pyrcz, Clayton V. Deutsch

Geostatistical reservoir modeling, Michael J. Pyrcz, Clayton V. Deutsch

Label
Geostatistical reservoir modeling
Title
Geostatistical reservoir modeling
Statement of responsibility
Michael J. Pyrcz, Clayton V. Deutsch
Creator
Contributor
Author
Subject
Language
eng
Cataloging source
E7B
http://library.link/vocab/creatorName
Pyrcz, Michael
Dewey number
553.2/82015195
Illustrations
illustrations
Index
index present
LC call number
TN870.53
LC item number
.P973 2014eb
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
http://library.link/vocab/relatedWorkOrContributorName
Deutsch, Clayton V.
http://library.link/vocab/subjectName
  • Hydrocarbon reservoirs
  • Petroleum
Label
Geostatistical reservoir modeling, Michael J. Pyrcz, Clayton V. Deutsch
Instantiates
Publication
Copyright
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier.
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent.
Contents
  • Key Concepts
  • Object-Based Simulation
  • 2.4.7.
  • Optimization Algorithms for Modeling
  • 2.4.8.
  • Accounting for Trends
  • 2.4.9.
  • Alternatives for Secondary Data Integration
  • 2.4.10.
  • Work Flow
  • 2.4.11.
  • 1.4.
  • Section Summary
  • 3.
  • Modeling Prerequisites
  • 3.1.
  • Data Inventory
  • 3.1.1.
  • Data Events
  • 3.1.2.
  • Well Data
  • 3.1.3.
  • Motivation for Reservoir Models
  • Seismic Data
  • 3.1.4.
  • Dynamic Data
  • 3.1.5.
  • Analog Data
  • 3.1.6.
  • Data Considerations
  • 3.1.7.
  • Section Summary
  • 3.2.
  • 1.5.
  • Conceptual Model
  • 3.2.1.
  • Conceptual Geological Model
  • 3.2.2.
  • Model Framework
  • 3.2.3.
  • Modeling Method Choice
  • 3.2.4.
  • Statistical Inputs and Geological Rules
  • 3.2.5.
  • Data for Reservoir Modeling
  • Work Flow
  • 3.2.6.
  • Section Summary
  • 3.3.
  • Problem Formulation
  • 3.3.1.
  • Goal and Purpose Definition
  • 3.3.2.
  • Modeling Work Constraints
  • 3.3.3.
  • 1.6.
  • Synthetic Paleo-basin
  • 3.3.4.
  • Modeling Work Flows
  • 3.3.5.
  • Reporting and Documentation
  • 3.3.6.
  • Work Flow
  • 3.3.7.
  • Section Summary
  • 4.
  • Common Work Flow
  • Modeling Methods
  • 4.1.
  • Large-Scale Modeling
  • 4.1.1.
  • Structure and Bounding Surfaces
  • 4.1.2.
  • Identification of Regions
  • 4.1.3.
  • Trend Model Construction
  • 4.1.4.
  • 1.7.
  • Multivariate Mapping
  • 4.1.5.
  • Summarization and Visualization
  • 4.1.6.
  • Section Summary
  • 4.2.
  • Variogram-Based Facies Modeling
  • 4.2.1.
  • Comments on Facies Modeling
  • 4.2.2.
  • Introductory Example
  • Sequential Indicator Simulation
  • 4.2.3.
  • Truncated Gaussian Simulation
  • 4.2.4.
  • Cleaning Cell-Based Facies Realizations
  • 4.2.5.
  • Work Flow
  • 4.2.6.
  • Section Summary
  • 4.3.
  • 1.8.
  • Multiple-Point Facies Modeling
  • 4.3.1.
  • Multiple-Point Simulation
  • 4.3.2.
  • Sequential Simulation with MPS
  • 4.3.3.
  • Input Statistics
  • 4.3.4.
  • Implementation Details
  • 4.3.5.
  • Machine generated contents note:
  • Work Flow Diagrams
  • Work Flow
  • 4.3.6.
  • Section Summary
  • 4.4.
  • Object-Based Facies Modeling
  • 4.4.1.
  • Background
  • 4.4.2.
  • Stochastic Shales
  • 4.4.3.
  • 2.
  • Fluvial Modeling
  • 4.4.4.
  • Nonfluvial Depositional Systems
  • 4.4.5.
  • Work Flow
  • 4.4.6.
  • Section Summary
  • 4.5.
  • Process-Mimicking Facies Modeling
  • 4.5.1.
  • Modeling Principles
  • Background
  • 4.5.2.
  • Process-Mimicking Modeling
  • 4.5.3.
  • Work Flow
  • 4.5.4.
  • Section Summary
  • 4.6.
  • Porosity and Permeability Modeling
  • 4.6.1.
  • 2.1.
  • Background
  • 4.6.2.
  • Gaussian Techniques for Porosity
  • 4.6.3.
  • Seismic Data in SGS for Porosity
  • 4.6.4.
  • Porosity/Permeability Transforms
  • 4.6.5.
  • Gaussian Techniques for Permeability
  • 4.6.6.
  • Preliminary Geological Modeling Concepts
  • Indicator Technique for Permeability
  • 4.6.7.
  • Work Flow
  • 4.6.8.
  • Section Summary
  • 4.7.
  • Optimization for Model Construction
  • 4.7.1.
  • Background
  • 4.7.2.
  • 2.1.1.
  • Simulated Annealing
  • 4.7.3.
  • Perturbation Mechanism
  • 4.7.4.
  • Update Objective Function
  • 4.7.5.
  • Decision Rule
  • 4.7.6.
  • Problem Areas
  • 4.7.7.
  • Story
  • Other Methods
  • 4.7.8.
  • Work Flow
  • 4.7.9.
  • Section Summary
  • 5.
  • Model Applications
  • 5.1.
  • Model Checking
  • 5.1.1.
  • 2.1.2.
  • Background
  • 5.1.2.
  • Minimum Acceptance Checks
  • 5.1.3.
  • High-Order Checks
  • 5.1.4.
  • Cross Validation and the Jackknife
  • 5.1.5.
  • Checking Distributions of Uncertainty
  • 5.1.6.
  • Geological Models
  • Work Flow
  • 5.1.7.
  • Section Summary
  • 5.2.
  • Model Post-processing
  • 5.2.1.
  • Background
  • 5.2.2.
  • Model Modification
  • 5.2.3.
  • 2.1.3.
  • Model Scaling
  • 5.2.4.
  • Pointwise Summary Models
  • 5.2.5.
  • Joint Summary Models
  • 5.2.6.
  • Work Flow
  • 5.2.7.
  • Section Summary
  • 5.3.
  • 1.
  • Geological Model Overview
  • Uncertainty Management
  • 5.3.1.
  • Background
  • 5.3.2.
  • Uncertainty Considerations
  • 5.3.3.
  • How Many Realizations?
  • 5.3.4.
  • Summarizing Uncertainty
  • 5.3.5.
  • 2.1.4.
  • Uncertainty Versus Well Spacing
  • 5.3.6.
  • Case for Geometric Criteria
  • 5.3.7.
  • Ranking Realizations
  • 5.3.8.
  • Decision Making with Uncertainty
  • 5.3.9.
  • Work Flow
  • 5.3.10.
  • Basin Formation and Filling
  • Section Summary
  • 6.
  • Special Topics
  • 6.1.
  • Unstructured Grids
  • 6.2.
  • Continuous Variable Heterogeneity
  • 6.3.
  • More Estimation Methods
  • 6.4.
  • 2.1.5.
  • Spectral Methods
  • 6.5.
  • Surface-Based Modeling
  • 6.6.
  • Ensemble Kalman Filtering
  • 6.7.
  • Advanced Geological Characterization
  • 6.8.
  • Other Emerging Techniques
  • 6.9.
  • Reservoir Architecture
  • Final Thoughts
  • A.
  • Glossary and Notation
  • A.1.
  • Glossary
  • A.2.
  • Notation
  • 2.1.6.
  • Example Stories and Reservoir Modeling Significance
  • 2.1.7.
  • Section Summary
  • 2.2.
  • Introduction
  • Preliminary Statistical Concepts
  • 2.2.1.
  • Geological Populations and Stationarity
  • 2.2.2.
  • Notation and Definitions
  • 2.2.3.
  • Bivariate Distributions
  • 2.2.4.
  • Q--Q Plots and Data Transformation
  • 2.2.5.
  • 1.1.
  • Data Transformation
  • 2.2.6.
  • Declustering and Debiasing
  • 2.2.7.
  • Histogram and Cross-Plot Smoothing
  • 2.2.8.
  • Monte Carlo Simulation
  • 2.2.9.
  • Parameter Uncertainty
  • 2.2.10.
  • Comments on Second Edition
  • Bayesian Statistics
  • 2.2.11.
  • Work Flow
  • 2.2.12.
  • Section Summary
  • 2.3.
  • Quantifying Spatial Correlation
  • 2.3.1.
  • Random Function Concept
  • 2.3.2.
  • 1.2.
  • Calculating Experimental Variograms
  • 2.3.3.
  • Interpreting Experimental Variograms
  • 2.3.4.
  • Horizontal Variograms
  • 2.3.5.
  • Variogram Modeling
  • 2.3.6.
  • Cross Variograms
  • 2.3.7.
  • Plan for the Book
  • Multiple-Point Statistics
  • 2.3.8.
  • Volume Variance Relations
  • 2.3.9.
  • Work Flow
  • 2.3.10.
  • Section Summary
  • 2.4.
  • Preliminary Mapping Concepts
  • 2.4.1.
  • 1.3.
  • Kriging and Cokriging
  • 2.4.2.
  • Sequential Gaussian Simulation
  • 2.4.3.
  • Indicator Formalism
  • 2.4.4.
  • P-Field Methods
  • 2.4.5.
  • Multiple-Point Simulation
  • 2.4.6.
Control code
874149979
Dimensions
unknown
Edition
Second edition.
Extent
1 online resource (449 pages)
Form of item
online
Isbn
9780199358830
Isbn Type
(e-book)
Media category
computer
Media MARC source
rdamedia.
Media type code
  • c
Other physical details
illustrations.
Specific material designation
remote
System control number
(OCoLC)874149979
Label
Geostatistical reservoir modeling, Michael J. Pyrcz, Clayton V. Deutsch
Publication
Copyright
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier.
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent.
Contents
  • Key Concepts
  • Object-Based Simulation
  • 2.4.7.
  • Optimization Algorithms for Modeling
  • 2.4.8.
  • Accounting for Trends
  • 2.4.9.
  • Alternatives for Secondary Data Integration
  • 2.4.10.
  • Work Flow
  • 2.4.11.
  • 1.4.
  • Section Summary
  • 3.
  • Modeling Prerequisites
  • 3.1.
  • Data Inventory
  • 3.1.1.
  • Data Events
  • 3.1.2.
  • Well Data
  • 3.1.3.
  • Motivation for Reservoir Models
  • Seismic Data
  • 3.1.4.
  • Dynamic Data
  • 3.1.5.
  • Analog Data
  • 3.1.6.
  • Data Considerations
  • 3.1.7.
  • Section Summary
  • 3.2.
  • 1.5.
  • Conceptual Model
  • 3.2.1.
  • Conceptual Geological Model
  • 3.2.2.
  • Model Framework
  • 3.2.3.
  • Modeling Method Choice
  • 3.2.4.
  • Statistical Inputs and Geological Rules
  • 3.2.5.
  • Data for Reservoir Modeling
  • Work Flow
  • 3.2.6.
  • Section Summary
  • 3.3.
  • Problem Formulation
  • 3.3.1.
  • Goal and Purpose Definition
  • 3.3.2.
  • Modeling Work Constraints
  • 3.3.3.
  • 1.6.
  • Synthetic Paleo-basin
  • 3.3.4.
  • Modeling Work Flows
  • 3.3.5.
  • Reporting and Documentation
  • 3.3.6.
  • Work Flow
  • 3.3.7.
  • Section Summary
  • 4.
  • Common Work Flow
  • Modeling Methods
  • 4.1.
  • Large-Scale Modeling
  • 4.1.1.
  • Structure and Bounding Surfaces
  • 4.1.2.
  • Identification of Regions
  • 4.1.3.
  • Trend Model Construction
  • 4.1.4.
  • 1.7.
  • Multivariate Mapping
  • 4.1.5.
  • Summarization and Visualization
  • 4.1.6.
  • Section Summary
  • 4.2.
  • Variogram-Based Facies Modeling
  • 4.2.1.
  • Comments on Facies Modeling
  • 4.2.2.
  • Introductory Example
  • Sequential Indicator Simulation
  • 4.2.3.
  • Truncated Gaussian Simulation
  • 4.2.4.
  • Cleaning Cell-Based Facies Realizations
  • 4.2.5.
  • Work Flow
  • 4.2.6.
  • Section Summary
  • 4.3.
  • 1.8.
  • Multiple-Point Facies Modeling
  • 4.3.1.
  • Multiple-Point Simulation
  • 4.3.2.
  • Sequential Simulation with MPS
  • 4.3.3.
  • Input Statistics
  • 4.3.4.
  • Implementation Details
  • 4.3.5.
  • Machine generated contents note:
  • Work Flow Diagrams
  • Work Flow
  • 4.3.6.
  • Section Summary
  • 4.4.
  • Object-Based Facies Modeling
  • 4.4.1.
  • Background
  • 4.4.2.
  • Stochastic Shales
  • 4.4.3.
  • 2.
  • Fluvial Modeling
  • 4.4.4.
  • Nonfluvial Depositional Systems
  • 4.4.5.
  • Work Flow
  • 4.4.6.
  • Section Summary
  • 4.5.
  • Process-Mimicking Facies Modeling
  • 4.5.1.
  • Modeling Principles
  • Background
  • 4.5.2.
  • Process-Mimicking Modeling
  • 4.5.3.
  • Work Flow
  • 4.5.4.
  • Section Summary
  • 4.6.
  • Porosity and Permeability Modeling
  • 4.6.1.
  • 2.1.
  • Background
  • 4.6.2.
  • Gaussian Techniques for Porosity
  • 4.6.3.
  • Seismic Data in SGS for Porosity
  • 4.6.4.
  • Porosity/Permeability Transforms
  • 4.6.5.
  • Gaussian Techniques for Permeability
  • 4.6.6.
  • Preliminary Geological Modeling Concepts
  • Indicator Technique for Permeability
  • 4.6.7.
  • Work Flow
  • 4.6.8.
  • Section Summary
  • 4.7.
  • Optimization for Model Construction
  • 4.7.1.
  • Background
  • 4.7.2.
  • 2.1.1.
  • Simulated Annealing
  • 4.7.3.
  • Perturbation Mechanism
  • 4.7.4.
  • Update Objective Function
  • 4.7.5.
  • Decision Rule
  • 4.7.6.
  • Problem Areas
  • 4.7.7.
  • Story
  • Other Methods
  • 4.7.8.
  • Work Flow
  • 4.7.9.
  • Section Summary
  • 5.
  • Model Applications
  • 5.1.
  • Model Checking
  • 5.1.1.
  • 2.1.2.
  • Background
  • 5.1.2.
  • Minimum Acceptance Checks
  • 5.1.3.
  • High-Order Checks
  • 5.1.4.
  • Cross Validation and the Jackknife
  • 5.1.5.
  • Checking Distributions of Uncertainty
  • 5.1.6.
  • Geological Models
  • Work Flow
  • 5.1.7.
  • Section Summary
  • 5.2.
  • Model Post-processing
  • 5.2.1.
  • Background
  • 5.2.2.
  • Model Modification
  • 5.2.3.
  • 2.1.3.
  • Model Scaling
  • 5.2.4.
  • Pointwise Summary Models
  • 5.2.5.
  • Joint Summary Models
  • 5.2.6.
  • Work Flow
  • 5.2.7.
  • Section Summary
  • 5.3.
  • 1.
  • Geological Model Overview
  • Uncertainty Management
  • 5.3.1.
  • Background
  • 5.3.2.
  • Uncertainty Considerations
  • 5.3.3.
  • How Many Realizations?
  • 5.3.4.
  • Summarizing Uncertainty
  • 5.3.5.
  • 2.1.4.
  • Uncertainty Versus Well Spacing
  • 5.3.6.
  • Case for Geometric Criteria
  • 5.3.7.
  • Ranking Realizations
  • 5.3.8.
  • Decision Making with Uncertainty
  • 5.3.9.
  • Work Flow
  • 5.3.10.
  • Basin Formation and Filling
  • Section Summary
  • 6.
  • Special Topics
  • 6.1.
  • Unstructured Grids
  • 6.2.
  • Continuous Variable Heterogeneity
  • 6.3.
  • More Estimation Methods
  • 6.4.
  • 2.1.5.
  • Spectral Methods
  • 6.5.
  • Surface-Based Modeling
  • 6.6.
  • Ensemble Kalman Filtering
  • 6.7.
  • Advanced Geological Characterization
  • 6.8.
  • Other Emerging Techniques
  • 6.9.
  • Reservoir Architecture
  • Final Thoughts
  • A.
  • Glossary and Notation
  • A.1.
  • Glossary
  • A.2.
  • Notation
  • 2.1.6.
  • Example Stories and Reservoir Modeling Significance
  • 2.1.7.
  • Section Summary
  • 2.2.
  • Introduction
  • Preliminary Statistical Concepts
  • 2.2.1.
  • Geological Populations and Stationarity
  • 2.2.2.
  • Notation and Definitions
  • 2.2.3.
  • Bivariate Distributions
  • 2.2.4.
  • Q--Q Plots and Data Transformation
  • 2.2.5.
  • 1.1.
  • Data Transformation
  • 2.2.6.
  • Declustering and Debiasing
  • 2.2.7.
  • Histogram and Cross-Plot Smoothing
  • 2.2.8.
  • Monte Carlo Simulation
  • 2.2.9.
  • Parameter Uncertainty
  • 2.2.10.
  • Comments on Second Edition
  • Bayesian Statistics
  • 2.2.11.
  • Work Flow
  • 2.2.12.
  • Section Summary
  • 2.3.
  • Quantifying Spatial Correlation
  • 2.3.1.
  • Random Function Concept
  • 2.3.2.
  • 1.2.
  • Calculating Experimental Variograms
  • 2.3.3.
  • Interpreting Experimental Variograms
  • 2.3.4.
  • Horizontal Variograms
  • 2.3.5.
  • Variogram Modeling
  • 2.3.6.
  • Cross Variograms
  • 2.3.7.
  • Plan for the Book
  • Multiple-Point Statistics
  • 2.3.8.
  • Volume Variance Relations
  • 2.3.9.
  • Work Flow
  • 2.3.10.
  • Section Summary
  • 2.4.
  • Preliminary Mapping Concepts
  • 2.4.1.
  • 1.3.
  • Kriging and Cokriging
  • 2.4.2.
  • Sequential Gaussian Simulation
  • 2.4.3.
  • Indicator Formalism
  • 2.4.4.
  • P-Field Methods
  • 2.4.5.
  • Multiple-Point Simulation
  • 2.4.6.
Control code
874149979
Dimensions
unknown
Edition
Second edition.
Extent
1 online resource (449 pages)
Form of item
online
Isbn
9780199358830
Isbn Type
(e-book)
Media category
computer
Media MARC source
rdamedia.
Media type code
  • c
Other physical details
illustrations.
Specific material designation
remote
System control number
(OCoLC)874149979

Library Locations

    • Curtis Laws Wilson LibraryBorrow it
      400 West 14th Street, Rolla, MO, 65409, US
      37.955220 -91.772210
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