Geostatistical reservoir modeling /:
A revised edition that provides a full update on the most current methods, tools, and research in petroleum geostatistics.
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Weitere Verfasser: | |
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Oxford :
Oxford University Press,
[2014]
|
| Ausgabe: | 2nd edition. |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Zusammenfassung: | A revised edition that provides a full update on the most current methods, tools, and research in petroleum geostatistics. |
| Beschreibung: | 1 online resource |
| Bibliographie: | Includes bibliographical references and index. |
| ISBN: | 9780199358830 0199358834 |
Internformat
MARC
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| 049 | |a MAIN | ||
| 100 | 1 | |a Deutsch, Clayton V. | |
| 245 | 1 | 0 | |a Geostatistical reservoir modeling / |c Clayton Deutsch, Michael Pyrcz. |
| 250 | |a 2nd edition. | ||
| 264 | 1 | |a Oxford : |b Oxford University Press, |c [2014] | |
| 300 | |a 1 online resource | ||
| 336 | |a text |b txt |2 rdacontent | ||
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| 504 | |a Includes bibliographical references and index. | ||
| 588 | 0 | |a Print version record. | |
| 505 | 0 | 0 | |g Machine generated contents note: |g 1. |t Introduction -- |g 1.1. |t Comments on Second Edition -- |g 1.2. |t Plan for the Book -- |g 1.3. |t Key Concepts -- |g 1.4. |t Motivation for Reservoir Models -- |g 1.5. |t Data for Reservoir Modeling -- |g 1.6. |t The Common Work Flow -- |g 1.7. |t An Introductory Example -- |g 1.8. |t Work Flow Diagrams -- |g 2. |t Modeling Principles -- |g 2.1. |t Preliminary Geological Modeling Concepts -- |g 2.1.1. |t The Story -- |g 2.1.2. |t Geological Models -- |g 2.1.3. |t Geological Model Overview -- |g 2.1.4. |t Basin Formation and Filling -- |g 2.1.5. |t Reservoir Architecture -- |g 2.1.6. |t Example Stories and Reservoir Modeling Significance -- |g 2.1.7. |t Section Summary -- |g 2.2. |t Preliminary Statistical Concepts -- |g 2.2.1. |t Geological Populations and Stationarity -- |g 2.2.2. |t Notation and Definitions -- |g 2.2.3. |t Bivariate Distributions -- |g 2.2.4. |t Q -- Q Plots and Data Transformation -- |g 2.2.5. |t Data Transformation -- |g 2.2.6. |t Declustering and Debiasing. |
| 505 | 0 | 0 | |g 2.2.7. |t Histogram and Cross-Plot Smoothing -- |g 2.2.8. |t Monte Carlo Simulation -- |g 2.2.9. |t Parameter Uncertainty -- |g 2.2.10. |t Bayesian Statistics -- |g 2.2.11. |t Work Flow -- |g 2.2.12. |t Section Summary -- |g 2.3. |t Quantifying Spatial Correlation -- |g 2.3.1. |t The Random Function Concept -- |g 2.3.2. |t Calculating Experimental Variograms -- |g 2.3.3. |t Interpreting Experimental Variograms -- |g 2.3.4. |t Horizontal Variograms -- |g 2.3.5. |t Variogram Modeling -- |g 2.3.6. |t Cross Variograms -- |g 2.3.7. |t Multiple-Point Statistics -- |g 2.3.8. |t Volume Variance Relations -- |g 2.3.9. |t Work Flow -- |g 2.3.10. |t Section Summary -- |g 2.4. |t Preliminary Mapping Concepts -- |g 2.4.1. |t Kriging and Cokriging -- |g 2.4.2. |t Sequential Gaussian Simulation -- |g 2.4.3. |t Indicator Formalism -- |g 2.4.4. |t P-Field Methods -- |g 2.4.5. |t Multiple-Point Simulation -- |g 2.4.6. |t Object-Based Simulation -- |g 2.4.7. |t Optimization Algorithms for Modeling -- |g 2.4.8. |t Accounting for Trends -- |g 2.4.9. |t Alternatives for Secondary Data Integration. |
| 505 | 0 | 0 | |g 2.4.10. |t Work Flow -- |g 2.4.11. |t Section Summary -- |g 3. |t Modeling Prerequisites -- |g 3.1. |t Data Inventory -- |g 3.1.1. |t Data Events -- |g 3.1.2. |t Well Data -- |g 3.1.3. |t Seismic Data -- |g 3.1.4. |t Dynamic Data -- |g 3.1.5. |t Analog Data -- |g 3.1.6. |t Data Considerations -- |g 3.1.7. |t Section Summary -- |g 3.2. |t Conceptual Model -- |g 3.2.1. |t Conceptual Geological Model -- |g 3.2.2. |t Model Framework -- |g 3.2.3. |t Modeling Method Choice -- |g 3.2.4. |t Statistical Inputs and Geological Rules -- |g 3.2.5. |t Work Flow -- |g 3.2.6. |t Section Summary -- |g 3.3. |t Problem Formulation -- |g 3.3.1. |t Goal and Purpose Definition -- |g 3.3.2. |t Modeling Work Constraints -- |g 3.3.3. |t Synthetic Paleo-basin -- |g 3.3.4. |t Modeling Work Flows -- |g 3.3.5. |t Reporting and Documentation -- |g 3.3.6. |t Work Flow -- |g 3.3.7. |t Section Summary -- |g 4. |t Modeling Methods -- |g 4.1. |t Large-Scale Modeling -- |g 4.1.1. |t Structure and Bounding Surfaces -- |g 4.1.2. |t Identification of Regions -- |g 4.1.3. |t Trend Model Construction -- |g 4.1.4. |t Multivariate Mapping. |
| 505 | 0 | 0 | |g 4.1.5. |t Summarization and Visualization -- |g 4.1.6. |t Section Summary -- |g 4.2. |t Variogram-Based Facies Modeling -- |g 4.2.1. |t Comments on Facies Modeling -- |g 4.2.2. |t Sequential Indicator Simulation -- |g 4.2.3. |t Truncated Gaussian Simulation -- |g 4.2.4. |t Cleaning Cell-Based Facies Realizations -- |g 4.2.5. |t Work Flow -- |g 4.2.6. |t Section Summary -- |g 4.3. |t Multiple-Point Facies Modeling -- |g 4.3.1. |t Multiple-Point Simulation -- |g 4.3.2. |t Sequential Simulation with MPS -- |g 4.3.3. |t Input Statistics -- |g 4.3.4. |t Implementation Details -- |g 4.3.5. |t Work Flow -- |g 4.3.6. |t Section Summary -- |g 4.4. |t Object-Based Facies Modeling -- |g 4.4.1. |t Background -- |g 4.4.2. |t Stochastic Shales -- |g 4.4.3. |t Fluvial Modeling -- |g 4.4.4. |t Nonfluvial Depositional Systems -- |g 4.4.5. |t Work Flow -- |g 4.4.6. |t Section Summary -- |g 4.5. |t Process-Mimicking Facies Modeling -- |g 4.5.1. |t Background -- |g 4.5.2. |t Process-Mimicking Modeling -- |g 4.5.3. |t Work Flow -- |g 4.5.4. |t Section Summary -- |g 4.6. |t Porosity and Permeability Modeling. |
| 505 | 0 | 0 | |g 4.6.1. |t Background -- |g 4.6.2. |t Gaussian Techniques for Porosity -- |g 4.6.3. |t Seismic Data in SGS for Porosity -- |g 4.6.4. |t Porosity/Permeability Transforms -- |g 4.6.5. |t Gaussian Techniques for Permeability -- |g 4.6.6. |t Indicator Technique for Permeability -- |g 4.6.7. |t Work Flow -- |g 4.6.8. |t Section Summary -- |g 4.7. |t Optimization for Model Construction -- |g 4.7.1. |t Background -- |g 4.7.2. |t Simulated Annealing -- |g 4.7.3. |t Perturbation Mechanism -- |g 4.7.4. |t Update Objective Function -- |g 4.7.5. |t Decision Rule -- |g 4.7.6. |t Problem Areas -- |g 4.7.7. |t Other Methods -- |g 4.7.8. |t Work Flow -- |g 4.7.9. |t Section Summary -- |g 5. |t Model Applications -- |g 5.1. |t Model Checking -- |g 5.1.1. |t Background -- |g 5.1.2. |t Minimum Acceptance Checks -- |g 5.1.3. |t High-Order Checks -- |g 5.1.4. |t Cross Validation and the Jackknife -- |g 5.1.5. |t Checking Distributions of Uncertainty -- |g 5.1.6. |t Work Flow -- |g 5.1.7. |t Section Summary -- |g 5.2. |t Model Post-processing -- |g 5.2.1. |t Background -- |g 5.2.2. |t Model Modification. |
| 505 | 0 | 0 | |g 5.2.3. |t Model Scaling -- |g 5.2.4. |t Pointwise Summary Models -- |g 5.2.5. |t Joint Summary Models -- |g 5.2.6. |t Work Flow -- |g 5.2.7. |t Section Summary -- |g 5.3. |t Uncertainty Management -- |g 5.3.1. |t Background -- |g 5.3.2. |t Uncertainty Considerations -- |g 5.3.3. |t How Many Realizations? -- |g 5.3.4. |t Summarizing Uncertainty -- |g 5.3.5. |t Uncertainty Versus Well Spacing -- |g 5.3.6. |t Case for Geometric Criteria -- |g 5.3.7. |t Ranking Realizations -- |g 5.3.8. |t Decision Making with Uncertainty -- |g 5.3.9. |t Work Flow -- |g 5.3.10. |t Section Summary -- |g 6. |t Special Topics -- |g 6.1. |t Unstructured Grids -- |g 6.2. |t Continuous Variable Heterogeneity -- |g 6.3. |t More Estimation Methods -- |g 6.4. |t Spectral Methods -- |g 6.5. |t Surface-Based Modeling -- |g 6.6. |t Ensemble Kalman Filtering -- |g 6.7. |t Advanced Geological Characterization -- |g 6.8. |t Other Emerging Techniques -- |g 6.9. |t Final Thoughts -- |g A. |t Glossary and Notation -- |g A.1. |t Glossary -- |g A.2. |t Notation. |
| 520 | |a A revised edition that provides a full update on the most current methods, tools, and research in petroleum geostatistics. | ||
| 650 | 0 | |a Hydrocarbon reservoirs |x Mathematical models. | |
| 650 | 0 | |a Petroleum |x Geology |x Statistical methods. | |
| 650 | 6 | |a Réservoirs d'hydrocarbures |x Modèles mathématiques. | |
| 650 | 6 | |a Pétrole |x Géologie |x Méthodes statistiques. | |
| 650 | 7 | |a NATURE |x Natural Resources. |2 bisacsh | |
| 650 | 7 | |a NATURE |x Rocks & Minerals. |2 bisacsh | |
| 650 | 7 | |a Hydrocarbon reservoirs |x Mathematical models |2 fast | |
| 650 | 7 | |a Petroleum |x Geology |x Statistical methods |2 fast | |
| 655 | 4 | |a Electronic book. | |
| 700 | 1 | |a Pyrcz, Michael. | |
| 758 | |i has work: |a Geostatistical reservoir modeling (Text) |1 https://id.oclc.org/worldcat/entity/E39PCFF8JBVHGD99dRmGr8wdw3 |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
| 776 | 0 | 8 | |i Print version: |a Deutsch, Clayton V. |t Geostatistical reservoir modeling. |b 2nd edition |z 9780199731442 |w (DLC) 2013031615 |w (OCoLC)855209593 |
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Datensatz im Suchindex
| DE-BY-FWS_katkey | ZDB-4-EBA-ocn868580476 |
|---|---|
| _version_ | 1813903632923361282 |
| adam_text | |
| any_adam_object | |
| author | Deutsch, Clayton V. |
| author2 | Pyrcz, Michael |
| author2_role | |
| author2_variant | m p mp |
| author_facet | Deutsch, Clayton V. Pyrcz, Michael |
| author_role | |
| author_sort | Deutsch, Clayton V. |
| author_variant | c v d cv cvd |
| building | Verbundindex |
| bvnumber | localFWS |
| callnumber-first | T - Technology |
| callnumber-label | TN870 |
| callnumber-raw | TN870.53 .D48 2014eb |
| callnumber-search | TN870.53 .D48 2014eb |
| callnumber-sort | TN 3870.53 D48 42014EB |
| callnumber-subject | TN - Mining Engineering and Metallurgy |
| collection | ZDB-4-EBA |
| contents | Introduction -- Comments on Second Edition -- Plan for the Book -- Key Concepts -- Motivation for Reservoir Models -- Data for Reservoir Modeling -- The Common Work Flow -- An Introductory Example -- Work Flow Diagrams -- Modeling Principles -- Preliminary Geological Modeling Concepts -- The Story -- Geological Models -- Geological Model Overview -- Basin Formation and Filling -- Reservoir Architecture -- Example Stories and Reservoir Modeling Significance -- Section Summary -- Preliminary Statistical Concepts -- Geological Populations and Stationarity -- Notation and Definitions -- Bivariate Distributions -- Q -- Q Plots and Data Transformation -- Data Transformation -- Declustering and Debiasing. Histogram and Cross-Plot Smoothing -- Monte Carlo Simulation -- Parameter Uncertainty -- Bayesian Statistics -- Work Flow -- Quantifying Spatial Correlation -- The Random Function Concept -- Calculating Experimental Variograms -- Interpreting Experimental Variograms -- Horizontal Variograms -- Variogram Modeling -- Cross Variograms -- Multiple-Point Statistics -- Volume Variance Relations -- Preliminary Mapping Concepts -- Kriging and Cokriging -- Sequential Gaussian Simulation -- Indicator Formalism -- P-Field Methods -- Multiple-Point Simulation -- Object-Based Simulation -- Optimization Algorithms for Modeling -- Accounting for Trends -- Alternatives for Secondary Data Integration. Modeling Prerequisites -- Data Inventory -- Data Events -- Well Data -- Seismic Data -- Dynamic Data -- Analog Data -- Data Considerations -- Conceptual Model -- Conceptual Geological Model -- Model Framework -- Modeling Method Choice -- Statistical Inputs and Geological Rules -- Problem Formulation -- Goal and Purpose Definition -- Modeling Work Constraints -- Synthetic Paleo-basin -- Modeling Work Flows -- Reporting and Documentation -- Modeling Methods -- Large-Scale Modeling -- Structure and Bounding Surfaces -- Identification of Regions -- Trend Model Construction -- Multivariate Mapping. Summarization and Visualization -- Variogram-Based Facies Modeling -- Comments on Facies Modeling -- Sequential Indicator Simulation -- Truncated Gaussian Simulation -- Cleaning Cell-Based Facies Realizations -- Multiple-Point Facies Modeling -- Sequential Simulation with MPS -- Input Statistics -- Implementation Details -- Object-Based Facies Modeling -- Background -- Stochastic Shales -- Fluvial Modeling -- Nonfluvial Depositional Systems -- Process-Mimicking Facies Modeling -- Process-Mimicking Modeling -- Porosity and Permeability Modeling. Gaussian Techniques for Porosity -- Seismic Data in SGS for Porosity -- Porosity/Permeability Transforms -- Gaussian Techniques for Permeability -- Indicator Technique for Permeability -- Optimization for Model Construction -- Simulated Annealing -- Perturbation Mechanism -- Update Objective Function -- Decision Rule -- Problem Areas -- Other Methods -- Model Applications -- Model Checking -- Minimum Acceptance Checks -- High-Order Checks -- Cross Validation and the Jackknife -- Checking Distributions of Uncertainty -- Model Post-processing -- Model Modification. Model Scaling -- Pointwise Summary Models -- Joint Summary Models -- Uncertainty Management -- Uncertainty Considerations -- How Many Realizations? -- Summarizing Uncertainty -- Uncertainty Versus Well Spacing -- Case for Geometric Criteria -- Ranking Realizations -- Decision Making with Uncertainty -- Special Topics -- Unstructured Grids -- Continuous Variable Heterogeneity -- More Estimation Methods -- Spectral Methods -- Surface-Based Modeling -- Ensemble Kalman Filtering -- Advanced Geological Characterization -- Other Emerging Techniques -- Final Thoughts -- Glossary and Notation -- Glossary -- Notation. |
| ctrlnum | (OCoLC)868580476 |
| dewey-full | 553.2/82015195 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 553 - Economic geology |
| dewey-raw | 553.2/82015195 |
| dewey-search | 553.2/82015195 |
| dewey-sort | 3553.2 882015195 |
| dewey-tens | 550 - Earth sciences |
| discipline | Geologie / Paläontologie |
| edition | 2nd edition. |
| format | Electronic eBook |
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code="g">2.3.9.</subfield><subfield code="t">Work Flow --</subfield><subfield code="g">2.3.10.</subfield><subfield code="t">Section Summary --</subfield><subfield code="g">2.4.</subfield><subfield code="t">Preliminary Mapping Concepts --</subfield><subfield code="g">2.4.1.</subfield><subfield code="t">Kriging and Cokriging --</subfield><subfield code="g">2.4.2.</subfield><subfield code="t">Sequential Gaussian Simulation --</subfield><subfield code="g">2.4.3.</subfield><subfield code="t">Indicator Formalism --</subfield><subfield code="g">2.4.4.</subfield><subfield code="t">P-Field Methods --</subfield><subfield code="g">2.4.5.</subfield><subfield code="t">Multiple-Point Simulation --</subfield><subfield code="g">2.4.6.</subfield><subfield code="t">Object-Based Simulation --</subfield><subfield code="g">2.4.7.</subfield><subfield code="t">Optimization Algorithms for Modeling --</subfield><subfield code="g">2.4.8.</subfield><subfield code="t">Accounting for Trends --</subfield><subfield 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| genre | Electronic book. |
| genre_facet | Electronic book. |
| id | ZDB-4-EBA-ocn868580476 |
| illustrated | Not Illustrated |
| indexdate | 2024-10-25T16:21:46Z |
| institution | BVB |
| isbn | 9780199358830 0199358834 |
| language | English |
| oclc_num | 868580476 |
| open_access_boolean | |
| owner | MAIN |
| owner_facet | MAIN |
| physical | 1 online resource |
| psigel | ZDB-4-EBA |
| publishDate | 2014 |
| publishDateSearch | 2014 |
| publishDateSort | 2014 |
| publisher | Oxford University Press, |
| record_format | marc |
| spelling | Deutsch, Clayton V. Geostatistical reservoir modeling / Clayton Deutsch, Michael Pyrcz. 2nd edition. Oxford : Oxford University Press, [2014] 1 online resource text txt rdacontent computer c rdamedia online resource cr rdacarrier Includes bibliographical references and index. Print version record. Machine generated contents note: 1. Introduction -- 1.1. Comments on Second Edition -- 1.2. Plan for the Book -- 1.3. Key Concepts -- 1.4. Motivation for Reservoir Models -- 1.5. Data for Reservoir Modeling -- 1.6. The Common Work Flow -- 1.7. An Introductory Example -- 1.8. Work Flow Diagrams -- 2. Modeling Principles -- 2.1. Preliminary Geological Modeling Concepts -- 2.1.1. The Story -- 2.1.2. Geological Models -- 2.1.3. Geological Model Overview -- 2.1.4. Basin Formation and Filling -- 2.1.5. Reservoir Architecture -- 2.1.6. Example Stories and Reservoir Modeling Significance -- 2.1.7. Section Summary -- 2.2. 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. 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. Bayesian Statistics -- 2.2.11. Work Flow -- 2.2.12. Section Summary -- 2.3. Quantifying Spatial Correlation -- 2.3.1. The Random Function Concept -- 2.3.2. 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. 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. 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. 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. Section Summary -- 3. Modeling Prerequisites -- 3.1. Data Inventory -- 3.1.1. Data Events -- 3.1.2. Well Data -- 3.1.3. Seismic Data -- 3.1.4. Dynamic Data -- 3.1.5. Analog Data -- 3.1.6. Data Considerations -- 3.1.7. Section Summary -- 3.2. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. Other Methods -- 4.7.8. Work Flow -- 4.7.9. Section Summary -- 5. Model Applications -- 5.1. Model Checking -- 5.1.1. 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. Work Flow -- 5.1.7. Section Summary -- 5.2. Model Post-processing -- 5.2.1. Background -- 5.2.2. Model Modification. 5.2.3. 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. 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. 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. Section Summary -- 6. Special Topics -- 6.1. Unstructured Grids -- 6.2. Continuous Variable Heterogeneity -- 6.3. More Estimation Methods -- 6.4. Spectral Methods -- 6.5. Surface-Based Modeling -- 6.6. Ensemble Kalman Filtering -- 6.7. Advanced Geological Characterization -- 6.8. Other Emerging Techniques -- 6.9. Final Thoughts -- A. Glossary and Notation -- A.1. Glossary -- A.2. Notation. A revised edition that provides a full update on the most current methods, tools, and research in petroleum geostatistics. Hydrocarbon reservoirs Mathematical models. Petroleum Geology Statistical methods. Réservoirs d'hydrocarbures Modèles mathématiques. Pétrole Géologie Méthodes statistiques. NATURE Natural Resources. bisacsh NATURE Rocks & Minerals. bisacsh Hydrocarbon reservoirs Mathematical models fast Petroleum Geology Statistical methods fast Electronic book. Pyrcz, Michael. has work: Geostatistical reservoir modeling (Text) https://id.oclc.org/worldcat/entity/E39PCFF8JBVHGD99dRmGr8wdw3 https://id.oclc.org/worldcat/ontology/hasWork Print version: Deutsch, Clayton V. Geostatistical reservoir modeling. 2nd edition 9780199731442 (DLC) 2013031615 (OCoLC)855209593 FWS01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=688155 Volltext CBO01 ZDB-4-EBA FWS_PDA_EBA https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=688155 Volltext |
| spellingShingle | Deutsch, Clayton V. Geostatistical reservoir modeling / Introduction -- Comments on Second Edition -- Plan for the Book -- Key Concepts -- Motivation for Reservoir Models -- Data for Reservoir Modeling -- The Common Work Flow -- An Introductory Example -- Work Flow Diagrams -- Modeling Principles -- Preliminary Geological Modeling Concepts -- The Story -- Geological Models -- Geological Model Overview -- Basin Formation and Filling -- Reservoir Architecture -- Example Stories and Reservoir Modeling Significance -- Section Summary -- Preliminary Statistical Concepts -- Geological Populations and Stationarity -- Notation and Definitions -- Bivariate Distributions -- Q -- Q Plots and Data Transformation -- Data Transformation -- Declustering and Debiasing. Histogram and Cross-Plot Smoothing -- Monte Carlo Simulation -- Parameter Uncertainty -- Bayesian Statistics -- Work Flow -- Quantifying Spatial Correlation -- The Random Function Concept -- Calculating Experimental Variograms -- Interpreting Experimental Variograms -- Horizontal Variograms -- Variogram Modeling -- Cross Variograms -- Multiple-Point Statistics -- Volume Variance Relations -- Preliminary Mapping Concepts -- Kriging and Cokriging -- Sequential Gaussian Simulation -- Indicator Formalism -- P-Field Methods -- Multiple-Point Simulation -- Object-Based Simulation -- Optimization Algorithms for Modeling -- Accounting for Trends -- Alternatives for Secondary Data Integration. Modeling Prerequisites -- Data Inventory -- Data Events -- Well Data -- Seismic Data -- Dynamic Data -- Analog Data -- Data Considerations -- Conceptual Model -- Conceptual Geological Model -- Model Framework -- Modeling Method Choice -- Statistical Inputs and Geological Rules -- Problem Formulation -- Goal and Purpose Definition -- Modeling Work Constraints -- Synthetic Paleo-basin -- Modeling Work Flows -- Reporting and Documentation -- Modeling Methods -- Large-Scale Modeling -- Structure and Bounding Surfaces -- Identification of Regions -- Trend Model Construction -- Multivariate Mapping. Summarization and Visualization -- Variogram-Based Facies Modeling -- Comments on Facies Modeling -- Sequential Indicator Simulation -- Truncated Gaussian Simulation -- Cleaning Cell-Based Facies Realizations -- Multiple-Point Facies Modeling -- Sequential Simulation with MPS -- Input Statistics -- Implementation Details -- Object-Based Facies Modeling -- Background -- Stochastic Shales -- Fluvial Modeling -- Nonfluvial Depositional Systems -- Process-Mimicking Facies Modeling -- Process-Mimicking Modeling -- Porosity and Permeability Modeling. Gaussian Techniques for Porosity -- Seismic Data in SGS for Porosity -- Porosity/Permeability Transforms -- Gaussian Techniques for Permeability -- Indicator Technique for Permeability -- Optimization for Model Construction -- Simulated Annealing -- Perturbation Mechanism -- Update Objective Function -- Decision Rule -- Problem Areas -- Other Methods -- Model Applications -- Model Checking -- Minimum Acceptance Checks -- High-Order Checks -- Cross Validation and the Jackknife -- Checking Distributions of Uncertainty -- Model Post-processing -- Model Modification. Model Scaling -- Pointwise Summary Models -- Joint Summary Models -- Uncertainty Management -- Uncertainty Considerations -- How Many Realizations? -- Summarizing Uncertainty -- Uncertainty Versus Well Spacing -- Case for Geometric Criteria -- Ranking Realizations -- Decision Making with Uncertainty -- Special Topics -- Unstructured Grids -- Continuous Variable Heterogeneity -- More Estimation Methods -- Spectral Methods -- Surface-Based Modeling -- Ensemble Kalman Filtering -- Advanced Geological Characterization -- Other Emerging Techniques -- Final Thoughts -- Glossary and Notation -- Glossary -- Notation. Hydrocarbon reservoirs Mathematical models. Petroleum Geology Statistical methods. Réservoirs d'hydrocarbures Modèles mathématiques. Pétrole Géologie Méthodes statistiques. NATURE Natural Resources. bisacsh NATURE Rocks & Minerals. bisacsh Hydrocarbon reservoirs Mathematical models fast Petroleum Geology Statistical methods fast |
| title | Geostatistical reservoir modeling / |
| title_alt | Introduction -- Comments on Second Edition -- Plan for the Book -- Key Concepts -- Motivation for Reservoir Models -- Data for Reservoir Modeling -- The Common Work Flow -- An Introductory Example -- Work Flow Diagrams -- Modeling Principles -- Preliminary Geological Modeling Concepts -- The Story -- Geological Models -- Geological Model Overview -- Basin Formation and Filling -- Reservoir Architecture -- Example Stories and Reservoir Modeling Significance -- Section Summary -- Preliminary Statistical Concepts -- Geological Populations and Stationarity -- Notation and Definitions -- Bivariate Distributions -- Q -- Q Plots and Data Transformation -- Data Transformation -- Declustering and Debiasing. Histogram and Cross-Plot Smoothing -- Monte Carlo Simulation -- Parameter Uncertainty -- Bayesian Statistics -- Work Flow -- Quantifying Spatial Correlation -- The Random Function Concept -- Calculating Experimental Variograms -- Interpreting Experimental Variograms -- Horizontal Variograms -- Variogram Modeling -- Cross Variograms -- Multiple-Point Statistics -- Volume Variance Relations -- Preliminary Mapping Concepts -- Kriging and Cokriging -- Sequential Gaussian Simulation -- Indicator Formalism -- P-Field Methods -- Multiple-Point Simulation -- Object-Based Simulation -- Optimization Algorithms for Modeling -- Accounting for Trends -- Alternatives for Secondary Data Integration. Modeling Prerequisites -- Data Inventory -- Data Events -- Well Data -- Seismic Data -- Dynamic Data -- Analog Data -- Data Considerations -- Conceptual Model -- Conceptual Geological Model -- Model Framework -- Modeling Method Choice -- Statistical Inputs and Geological Rules -- Problem Formulation -- Goal and Purpose Definition -- Modeling Work Constraints -- Synthetic Paleo-basin -- Modeling Work Flows -- Reporting and Documentation -- Modeling Methods -- Large-Scale Modeling -- Structure and Bounding Surfaces -- Identification of Regions -- Trend Model Construction -- Multivariate Mapping. Summarization and Visualization -- Variogram-Based Facies Modeling -- Comments on Facies Modeling -- Sequential Indicator Simulation -- Truncated Gaussian Simulation -- Cleaning Cell-Based Facies Realizations -- Multiple-Point Facies Modeling -- Sequential Simulation with MPS -- Input Statistics -- Implementation Details -- Object-Based Facies Modeling -- Background -- Stochastic Shales -- Fluvial Modeling -- Nonfluvial Depositional Systems -- Process-Mimicking Facies Modeling -- Process-Mimicking Modeling -- Porosity and Permeability Modeling. Gaussian Techniques for Porosity -- Seismic Data in SGS for Porosity -- Porosity/Permeability Transforms -- Gaussian Techniques for Permeability -- Indicator Technique for Permeability -- Optimization for Model Construction -- Simulated Annealing -- Perturbation Mechanism -- Update Objective Function -- Decision Rule -- Problem Areas -- Other Methods -- Model Applications -- Model Checking -- Minimum Acceptance Checks -- High-Order Checks -- Cross Validation and the Jackknife -- Checking Distributions of Uncertainty -- Model Post-processing -- Model Modification. Model Scaling -- Pointwise Summary Models -- Joint Summary Models -- Uncertainty Management -- Uncertainty Considerations -- How Many Realizations? -- Summarizing Uncertainty -- Uncertainty Versus Well Spacing -- Case for Geometric Criteria -- Ranking Realizations -- Decision Making with Uncertainty -- Special Topics -- Unstructured Grids -- Continuous Variable Heterogeneity -- More Estimation Methods -- Spectral Methods -- Surface-Based Modeling -- Ensemble Kalman Filtering -- Advanced Geological Characterization -- Other Emerging Techniques -- Final Thoughts -- Glossary and Notation -- Glossary -- Notation. |
| title_auth | Geostatistical reservoir modeling / |
| title_exact_search | Geostatistical reservoir modeling / |
| title_full | Geostatistical reservoir modeling / Clayton Deutsch, Michael Pyrcz. |
| title_fullStr | Geostatistical reservoir modeling / Clayton Deutsch, Michael Pyrcz. |
| title_full_unstemmed | Geostatistical reservoir modeling / Clayton Deutsch, Michael Pyrcz. |
| title_short | Geostatistical reservoir modeling / |
| title_sort | geostatistical reservoir modeling |
| topic | Hydrocarbon reservoirs Mathematical models. Petroleum Geology Statistical methods. Réservoirs d'hydrocarbures Modèles mathématiques. Pétrole Géologie Méthodes statistiques. NATURE Natural Resources. bisacsh NATURE Rocks & Minerals. bisacsh Hydrocarbon reservoirs Mathematical models fast Petroleum Geology Statistical methods fast |
| topic_facet | Hydrocarbon reservoirs Mathematical models. Petroleum Geology Statistical methods. Réservoirs d'hydrocarbures Modèles mathématiques. Pétrole Géologie Méthodes statistiques. NATURE Natural Resources. NATURE Rocks & Minerals. Hydrocarbon reservoirs Mathematical models Petroleum Geology Statistical methods Electronic book. |
| url | https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=688155 |
| work_keys_str_mv | AT deutschclaytonv geostatisticalreservoirmodeling AT pyrczmichael geostatisticalreservoirmodeling |