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Alternative energy and shale gas encyclopedia / / edited by Jay H. Lehr ; Jack Keeley, senior editor ; Thomas B. Kingery, information technology
| Alternative energy and shale gas encyclopedia / / edited by Jay H. Lehr ; Jack Keeley, senior editor ; Thomas B. Kingery, information technology |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : Wiley, , 2016 |
| Descrizione fisica | 1 online resource (1801 p.) |
| Disciplina | 621.04203 |
| Collana | Wiley Series on Energy |
| Soggetto topico |
Renewable energy sources
Shale gas |
| ISBN |
1-119-06633-6
1-119-06635-2 1-119-06632-8 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
2.2 NUMERICAL WEATHER PREDICTION MODELS2.3 PERSISTENCE MODELS; 2.4 CHOOSING FORECAST PARAMETERS; 2.5 STATISTICAL AND NEURAL NETWORK METHODS; 2.6 ADAPTIVE NEURO-FUZZY INFERENCE SYSTEMS; 2.7 CASE STUDY; REFERENCES; 3 MAXIMIZING THE LOADING IN WIND TURBINE PLANTS: (A) THE BETZ LIMIT, (B) DUCTING THE TURBINE; 3.1 THE WIND TURBINE EFFICIENCY; 3.2 THE BETZ LIMIT; 3.3 THE DUCTED WIND TURBINE; REFERENCES; 4 MODELING WIND TURBINE WAKES FOR WIND FARMS; 4.1 INTRODUCTION; 4.2 EMPIRICAL METHODS TO ESTIMATE WAKE RECOVERY; 4.3 COMPUTATIONAL FLUID DYNAMICS; 4.4 ROTOR MODELING TECHNIQUES
7.6 ENVIRONMENTAL IMPACT7.7 CONCLUSIONS; 7.8 MARINE ENERGY2; NOTE; REFERENCES; 8 IMPACTS OF WIND FARMS ON WEATHER AND CLIMATE AT LOCAL AND GLOBAL SCALES; 8.1 OBSERVED IMPACTS; 8.2 HOW WIND TURBINES INTERACT WITH THE ATMOSPHERE; 8.3 HOW WIND FARMS ARE REPRESENTED IN WEATHER AND CLIMATE MODELS; 8.4 IMPACTS OF WIND FARMS ON LOCAL METEOROLOGY; 8.5 IMPACTS OF WIND FARMS ON REGIONAL AND GLOBAL CLIMATE; 8.6 MINIMIZING IMPACTS; 8.7 CONCLUSIONS AND DISCUSSIONS; REFERENCES; 9 POWER CURVES AND TURBULENT FLOW CHARACTERISTICS OF VERTICAL AXIS WIND TURBINES; 9.1 RESIDENTIAL AND SMALL BUSINESS WIND POWER 11.1 INTRODUCTION |
| Record Nr. | UNINA-9910136940303321 |
| Hoboken, New Jersey : , : Wiley, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Assessment of undiscovered continuous oil and shale-gas resources in the Bazhenov Formation of the West Siberian Basin Province, Russia, 2016
| Assessment of undiscovered continuous oil and shale-gas resources in the Bazhenov Formation of the West Siberian Basin Province, Russia, 2016 |
| Pubbl/distr/stampa | [Reston, Va.] : , : U.S. Department of the Interior, U.S. Geological Survey, , 2016 |
| Descrizione fisica | 1 online resource (2 unnumbered pages) : maps |
| Collana | Fact sheet |
| Soggetto topico |
Petroleum - Russia (Federation) - Siberia, Western
Shale gas - Russia (Federation) - Siberia, Western Petroleum Shale gas |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910708055303321 |
| [Reston, Va.] : , : U.S. Department of the Interior, U.S. Geological Survey, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Deep shale oil and gas / / James G. Speight, Ph.D., DSc, CD&W Inc., Laramie, WY, United States
| Deep shale oil and gas / / James G. Speight, Ph.D., DSc, CD&W Inc., Laramie, WY, United States |
| Autore | Speight James G. |
| Pubbl/distr/stampa | Cambridge, MA : , : Gulf Professional Publishing, , [2017] |
| Descrizione fisica | 1 online resource (x, 481 pages) : illustrations (some color), maps |
| Disciplina | 665.7 |
| Collana | Gale eBooks |
| Soggetto topico |
Hydraulic fracturing
Shale gas Shale oils Shale gas reservoirs Oil shale reserves |
| ISBN | 0-12-803098-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1. Gas and oil in tight formations -- 2. Reservoirs and reservoir fluids -- 3. Gas and oil resources in tight formations -- 4. Development and production -- 5. Hydraulic fracturing -- 6. Fluids management -- 7. Properties processing of gas from tight formations -- 8. Properties and processing of crude oil from tight formations -- 9. Environmental impact. |
| Record Nr. | UNINA-9910583400503321 |
Speight James G.
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| Cambridge, MA : , : Gulf Professional Publishing, , [2017] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Lithofacies Paleogeography and Geological Survey of Shale Gas / / Chuanlong Mou, [and many others]
| Lithofacies Paleogeography and Geological Survey of Shale Gas / / Chuanlong Mou, [and many others] |
| Autore | Mou Chuanlong |
| Edizione | [First edition.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature, , 2023 |
| Descrizione fisica | 1 online resource (xv, 255 pages) : illustrations some color |
| Disciplina | 553.285 |
| Collana | The China Geological Survey Series. |
| Soggetto topico |
Natural gas - Geology
Lithofacies Shale gas |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction -- Analysis of factors controlling shale gas enrichment -- Shale Gas Geological Survey -- Examples: Taking the Ordovician Wufeng Formation-Silurian Longmaxi -- Formation in Southern Sichuan and its periphery as an example -- Hirnantian Glaciation. |
| Record Nr. | UNINA-9910684560203321 |
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Mou Chuanlong
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| Singapore : , : Springer Nature, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Natural gas resources : hearing before the Committee on Energy and Natural Resources, United States Senate, One Hundred Thirteenth Congress, first session, to explore opportunities and challenges associated with America's natural gas resources, February 12, 2013
| Natural gas resources : hearing before the Committee on Energy and Natural Resources, United States Senate, One Hundred Thirteenth Congress, first session, to explore opportunities and challenges associated with America's natural gas resources, February 12, 2013 |
| Pubbl/distr/stampa | Washington : , : U.S. G.P.O., , 2013 |
| Descrizione fisica | 1 online resource (iii, 184 pages) |
| Collana | S. hrg. |
| Soggetto topico |
Natural gas reserves - United States
Gas industry - United States Shale gas - United States Hydraulic fracturing - United States Gas industry Hydraulic fracturing Natural gas reserves Shale gas |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Natural gas resources |
| Record Nr. | UNINA-9910704562203321 |
| Washington : , : U.S. G.P.O., , 2013 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Shale gas : new aspects and technologies / / edited by Ali Al-Juboury
| Shale gas : new aspects and technologies / / edited by Ali Al-Juboury |
| Pubbl/distr/stampa | London, England : , : IntechOpen, , [2018] |
| Descrizione fisica | 1 online resource (110 pages) |
| Disciplina | 622.3381 |
| Soggetto topico |
Shale gas
Shale gas industry |
| ISBN |
1-83881-479-5
1-78923-619-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Shale gas |
| Record Nr. | UNINA-9910317795503321 |
| London, England : , : IntechOpen, , [2018] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Unconventional Hydrocarbon Resources
| Unconventional Hydrocarbon Resources |
| Autore | Ouadfeul Sid-Ali |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Newark : , : John Wiley & Sons, Incorporated, , 2023 |
| Descrizione fisica | 1 online resource (320 pages) |
| Soggetto topico |
Artificial intelligence
Shale gas |
| ISBN |
9781119389385
1119389380 9781119389378 1119389372 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover -- Title Page -- Copyright Page -- Contents -- Preface -- Chapter 1 Predrill Pore Pressure Estimation in Shale Gas Reservoirs Using Seismic Genetic Inversion with an Example from the Barnett Shale -- 1.1 Introduction -- 1.2 Methods and Application to Barnett Shale -- 1.2.1 Geological Setting -- 1.2.2 Methods -- 1.3 Data Processing -- 1.4 Results Interpretation and Conclusions -- References -- Chapter 2 An Analysis of the Barnett Shale's Seismic Anisotropy's Role in the Exploration of Shale Gas Reservoirs (United States) -- 2.1 Introduction -- 2.2 Seismic Anisotropy -- 2.3 Application to Barnett Shale -- 2.3.1 Geological Setting -- 2.3.2 Data Analysis -- 2.4 Conclusions -- References -- Chapter 3 Wellbore Stability in Shale Gas Reservoirs with a Case Study from the Barnett Shale -- 3.1 Introduction -- 3.2 Wellbore Stability -- 3.2.1 Mechanical Stress -- 3.2.2 Chemical Interactions with the Drilling Fluid -- 3.2.3 Physical Interactions with the Drilling Fluid -- 3.3 Pore Pressure Estimation Using the Eaton's Model -- 3.4 Shale Play Geomechanics and Wellbore Stability -- 3.5 Application to Barnett Shale -- 3.5.1 Geological Context -- 3.5.2 Data Processing -- 3.6 Conclusion -- References -- Chapter 4 A Comparison of the Levenberg-Marquardt and Conjugate Gradient Learning Methods for Total Organic Carbon Prediction in the Barnett Shale Gas Reservoir -- 4.1 Introduction -- 4.2 Levenberg-Marquardt Learning Algorithm -- 4.3 Application to Barnett Shale -- 4.3.1 Geological Setting -- 4.3.2 Data Processing -- 4.3.3 Results Interpretation -- 4.4 Conclusions -- References -- Chapter 5 Identifying Sweet Spots in Shale Reservoirs -- 5.1 Introduction -- 5.2 Materials and Methods -- 5.3 Data for Two Distinct Types of Sweet Spot Identification Workflows -- 5.3.1 Workflow 5.1: Early-Phase Workflow Elements: Total Petroleum System Approach.
5.3.2 Workflow 5.2: Smaller-Scale Field-Level Tools and Techniques -- 5.4 Results: Two Integrative Workflows -- 5.4.1 Early-Phase Exploration Workflow -- 5.4.2 Later Phase Developmental, Including Refracing Workflow -- 5.5 Case Studies -- 5.5.1 Woodford Shale: Emphasis on Chemostratigraphy -- 5.5.2 Barnett Shale: Emphasis on Seismic Attributes -- 5.5.3 Eagle Ford Shale: Pattern Recognition/Deep Learning -- 5.6 Conclusion -- References -- Chapter 6 Surfactants in Shale Reservoirs -- 6.1 Introduction -- 6.2 Function of Surfactants -- 6.2.1 Drilling -- 6.2.2 Completion (Hydraulic Fracturing) -- 6.3 Materials and Methods -- 6.4 Characteristics of Shale Reservoirs -- 6.4.1 High Clay Mineral Content -- 6.4.2 Nano-Sized Pores -- 6.4.3 Mixed-Wettability Behavior -- 6.4.4 High Capillary Pressures -- 6.5 The Klinkenberg Correction -- 6.5.1 Klinkenberg Gas Slippage Measurement -- 6.6 Completion Chemicals to Consider in Addition to the Surfactant -- 6.6.1 Enhanced Oil Recovery (EOR) -- 6.6.2 Liquids-Rich Shale Plays After Initial Decline -- 6.7 Mono-Coating Proppant -- 6.7.1 Zwitterionic Coating -- 6.8 Dual-Coating Proppant -- 6.8.1 Outside Coating -- 6.8.2 Inner Coating -- 6.9 Dual Coating with Porous Proppant -- 6.9.1 Zwitterionic Outer Coating -- Inorganic Salt Inner Coating, Porous Core -- 6.10 Data -- 6.10.1 Types of Surfactants -- 6.11 Examples of Surfactants in Shale Plays -- 6.11.1 Bakken (Wang and Xu 2012) -- 6.11.2 Eagle Ford (He and Xu 2017) -- 6.11.3 Utica (Shuler et al. 2016) -- 6.12 Results -- 6.13 Shale Reservoirs, Gas, and Adsorption -- 6.14 Operational Conditions -- 6.15 Conclusions -- References -- Chapter 7 Neuro-Fuzzy Algorithm Classification of Ordovician Tight Reservoir Facies in Algeria -- 7.1 Introduction -- 7.2 Neuro-Fuzzy Classification -- 7.3 Results Discussion -- 7.4 Conclusion -- References. Chapter 8 Recognition of Lithology Automatically Utilizing a New Artificial Neural Network Algorithm -- 8.1 Introduction -- 8.2 Well-Logging Methods -- 8.2.1 Nuclear Well Logging -- 8.2.2 Neutron Well Logging -- 8.2.3 Sonic Well Logging -- 8.3 Use of ANN in the Oil Industry -- 8.4 Lithofacies Recognition -- 8.5 Log Interpretation -- 8.5.1 Methodology of Manual Interpretation -- 8.5.2 Results of Manual/Automatic Interpretation -- 8.6 Conclusion -- References -- Chapter 9 Construction of a New Model (ANNSVM) Compensator for the Low Resistivity Phenomena Saturation Computation Based on Logging Curves -- 9.1 Introduction -- 9.2 Field Geological Description -- 9.2.1 Conventional Interpretation -- 9.2.2 Reservoir Mineralogy -- 9.3 Low-Resistivity Phenomenon -- 9.3.1 Cross Plots Interpretation -- 9.3.2 NMR Logs Interpretation -- 9.3.3 Comparison Between Well-1 and Well-2 -- 9.3.4 Developed Logging Tools -- 9.3.5 Proposed ANNSVM Algorithm -- 9.4 Conclusions -- References -- Chapter 10 A Practical Workflow for Improving the Correlation of Sub-Seismic Geological Structures and Natural Fractures using Seismic Attributes -- 10.1 Introduction -- 10.2 Description of the Developed Workflow -- 10.3 Discussion -- 10.4 Conclusions -- References -- Chapter 11 Calculation of Petrophysical Parameter Curves for Nonconventional Reservoir Modeling and Characterization -- 11.1 Introduction -- 11.2 Proposed Methods -- 11.3 Results and Discussion -- 11.4 Conclusions -- References -- Chapter 12 Fuzzy Logic for Predicting Pore Pressure in Shale Gas Reservoirs With a Barnett Shale Application -- 12.1 Introduction -- 12.2 The Fuzzy Logic -- 12.3 Application to Barnett Shale -- 12.3.1 Geological Context -- 12.3.2 Data Processing -- 12.4 Results Interpretation and Conclusions -- References. Chapter 13 Using Well-Log Data, a Hidden Weight Optimization Method Neural Network Can Classify the Lithofacies of a Shale Gas Reservoir: Barnett Shale Application -- 13.1 Introduction -- 13.2 Artificial Neural Network -- 13.3 Hidden Weight Optimization Algorithm Neural -- 13.4 Geological Context of the Barnett Shale -- 13.5 Results Interpretation and Conclusions -- Bibliography -- Chapter 14 The Use of Pore Effective Compressibility for Quantitative Evaluation of Low Resistive Pays -- 14.1 Introduction -- 14.2 Low-Resistivity Pays in the Studied Basin -- 14.3 Water Saturation from Effective Pore Compressibility -- 14.4 Discussion -- 14.5 Conclusions -- Bibliography -- Chapter 15 The Influence of Pore Levels on Reservoir Quality Based on Rock Typing: A Case Study of Quartzite El Hamra, Algeria -- 15.1 Introduction -- 15.2 Quick Scan Method -- 15.3 Results -- 15.4 Discussion -- 15.5 Conclusions -- Bibliography -- Chapter 16 An Example from the Algerian Sahara Illustrates the Use of the Hydraulic Flow Unit Technique to Discriminate Fluid Flow Routes in Confined Sand Reservoirs -- 16.1 Introduction -- 16.2 Regional Geologic Setting -- 16.3 Statement of the Problem -- 16.3.1 Concept of HFU -- 16.3.2 HFU Zonation Process -- 16.4 Results and Discussion -- 16.4.1 FZI Method -- 16.4.2 FZI Method -- 16.5 Conclusions -- References -- Chapter 17 Integration of Rock Types and Hydraulic Flow Units for Reservoir Characterization. Application to Three Forks Formation, Williston Basin, North Dakota, USA -- 17.1 Introduction -- 17.2 Petrophysical Rock-Type Prediction -- 17.3 Rock Types' Classification Based on R35 Pore Throat Radius -- 17.3.1 Upper Three Forks -- 17.3.2 Middle Three Forks -- 17.3.3 Lower Three Forks -- 17.4 Determination of Hydraulic Flow Units -- 17.4.1 Upper Three Forks -- 17.4.2 Middle Three Forks -- 17.4.3 Lower Three Forks -- 17.5 Conclusion. References -- Chapter 18 Stress-Dependent Permeability and Porosity and Hysteresis. Application to the Three Forks Formation, Williston Basin, North Dakota, USA -- 18.1 Introduction -- 18.2 Database -- 18.3 Testing Procedure -- 18.3.1 Core Samples Cleaning and Drying -- 18.3.2 Permeability and Porosity Measurements -- 18.3.3 Mineral Composition Analysis -- 18.3.4 Scanning Electron Microscope -- 18.4 Results and Discussions -- 18.4.1 Stress-Dependent Permeability and Hysteresis -- 18.4.2 Permeability Evolution with Net Stress -- 18.4.3 Stress-Dependent Porosity and Hysteresis -- 18.4.4 Porosity Evolution with Net Stress -- 18.4.5 Permeability Evolution with Porosity -- 18.5 Conclusion -- References -- Chapter 19 Petrophysical Analysis of Three Forks Formation in Williston Basin, North Dakota, USA -- 19.1 Introduction -- 19.2 Petrophysical Database -- 19.2.1 Curve Editing and Environmental Correction -- 19.2.2 Preanalysis Processing -- 19.3 Methods and Background -- 19.3.1 Wireline Logs -- 19.3.2 Petrophysical Analysis Challenges -- 19.4 Petrophysical Analysis Results and Discussion -- 19.4.1 Upper Three Forks -- 19.4.2 Middle Three Forks -- 19.4.3 Lower Three Forks -- 19.5 Conclusion -- References -- Chapter 20 Water Saturation Prediction Using Machine Learning and Deep Learning. Application to Three Forks Formation in Williston Basin, North Dakota, USA -- 20.1 Introduction -- 20.2 Experimental Procedure and Methodology -- 20.2.1 Support Vector Machine Concepts -- 20.2.2 Preprocessing of the Dataset -- 20.2.3 Building SVR Model -- 20.2.4 Building Random Forest Regression Model -- 20.2.5 Building Deep Learning Model -- 20.2.6 Curve Reconstruction Using K.Mod -- 20.3 Results and Discussion -- 20.4 Conclusion -- References -- Appendix Hysteresis Testing and Mineralogy -- Index -- EULA. |
| Record Nr. | UNINA-9910877289503321 |
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Ouadfeul Sid-Ali
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| Newark : , : John Wiley & Sons, Incorporated, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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