Sustainable Geoscience for Natural Gas SubSurface Systems: The Fundamentals and Sustainable Advances in Natural Gas Science and Eng
Editat de David Wood, Jianchao Caien Limba Engleză Paperback – 3 noi 2021
- Includes structured case studies to illustrate how new principles can be applied in practical situations
- Helps readers understand advanced topics, including machine learning applications to optimize predictions, controls and improve knowledge-based applications
- Provides tactics to accelerate emission reductions
- Teaches gas fracturing mechanics aimed at reducing environmental impacts, along with enhanced oil recovery technologies that capture carbon dioxide
Preț: 1072.31 lei
Preț vechi: 1468.92 lei
-27% Nou
Puncte Express: 1608
Preț estimativ în valută:
205.24€ • 213.91$ • 170.85£
205.24€ • 213.91$ • 170.85£
Carte tipărită la comandă
Livrare economică 06-20 ianuarie 25
Preluare comenzi: 021 569.72.76
Specificații
ISBN-13: 9780323854658
ISBN-10: 0323854656
Pagini: 434
Ilustrații: 200 illustrations (100 in full color)
Dimensiuni: 191 x 235 mm
Greutate: 0.74 kg
Editura: ELSEVIER SCIENCE
Seria The Fundamentals and Sustainable Advances in Natural Gas Science and Eng
ISBN-10: 0323854656
Pagini: 434
Ilustrații: 200 illustrations (100 in full color)
Dimensiuni: 191 x 235 mm
Greutate: 0.74 kg
Editura: ELSEVIER SCIENCE
Seria The Fundamentals and Sustainable Advances in Natural Gas Science and Eng
Cuprins
1. Pore-scale characterization and fractal analysis for gas migration mechanisms in shale gas reservoirs
2. Three-dimensional gas property geological modelling and simulation
3. Acoustic, density and seismic attribute analysis to aid gas detection and delineation of reservoir properties
4. Integrated microfacies interpretations of large natural gas reservoirs combining qualitative and quantitative image analysis
5. Brittleness index predictions from Lower Barnett shale well-log data applying an optimized data matching algorithm at various sampling densities
6. Shale kerogen kinetics from multi-heating rate pyrolysis modelling with geological time-scale perspectives for petroleum generation
7. Application of few-shot semi-supervised deep learning in organic matter content logging evaluation
8. Microseismic analysis to aid gas reservoir characterization
9. Coal-bed methane reservoir characterization using well-log data
10. Characterization of gas hydrate reservoirs using well logs and X-ray CT scanning as resources and environmental hazards
11. Assessing the sustainability of potential gas hydrate exploitation projects by integrating commercial, environmental, social and technical considerations
12. Gas adsorption and reserve estimation for conventional and unconventional gas resources
13. Dataset Insight and Variable Influences Established Using Correlations, Regressions and Transparent Customized Formula Optimization
2. Three-dimensional gas property geological modelling and simulation
3. Acoustic, density and seismic attribute analysis to aid gas detection and delineation of reservoir properties
4. Integrated microfacies interpretations of large natural gas reservoirs combining qualitative and quantitative image analysis
5. Brittleness index predictions from Lower Barnett shale well-log data applying an optimized data matching algorithm at various sampling densities
6. Shale kerogen kinetics from multi-heating rate pyrolysis modelling with geological time-scale perspectives for petroleum generation
7. Application of few-shot semi-supervised deep learning in organic matter content logging evaluation
8. Microseismic analysis to aid gas reservoir characterization
9. Coal-bed methane reservoir characterization using well-log data
10. Characterization of gas hydrate reservoirs using well logs and X-ray CT scanning as resources and environmental hazards
11. Assessing the sustainability of potential gas hydrate exploitation projects by integrating commercial, environmental, social and technical considerations
12. Gas adsorption and reserve estimation for conventional and unconventional gas resources
13. Dataset Insight and Variable Influences Established Using Correlations, Regressions and Transparent Customized Formula Optimization