Sustainable Geoscience for Natural Gas SubSurface Systems
-10%
portes grátis
Sustainable Geoscience for Natural Gas SubSurface Systems
Cai, Jianchao; Wood, David
Gulf Publishing Company
11/2021
434
Mole
Inglês
9780323854658
15 a 20 dias
860
Descrição não disponível.
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
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
3D modeling; Acoustic impedance; Arrhenius first-order reactions; Brittleness; Carbonate and clastic microfacies; CBM well-log relationships; Climate change; Clustering/classification algorithms; Coal characterization; Coal gas content; Coal structure indices; Coal-bed methane; Coarse-detailed feature extraction; Constant-A kinetic models; Conventional gas resources; Correlation coefficients; Correlation-free prediction analysis; Customized formula optimization; Deep learning; Density; Development assessment protocol; Energy resource; Entropy weights; Error minimization; Established E versus LnA trends for shales; Feature influence; Feature quantification; Few-shot; Fracability; Fractal; Fractal theory; Fuzzy/intuitionistic TOPSIS; Gas adsorption; Gas detection; Gas hydrate; Gas reservoir; Geohazard; Geological model; Geomechanics; Gulf of Suez; Horizontal stress differentials; Hydraulic fracturing; Image arithmetic; Image enhancement; Immature Duvernay shale; Integrated deep learning model; Intelligent logging evaluation; Kerogen transformation processes; Large-field case studies; Machine learning; Machine learning transparency mineralogical and elastic influences; Microseismic geomechanics; Microseismic monitoring; Multicriteria decision analysis (MCDA); Multilinear regression; Multiple-heating rate pyrolysis peak fitting; Nonlinear functions; Organic carbon; Petrographic interpretation; Petroleum generation complexities; Petroleum-generation kinetics; Physical property; Pore pressure prediction; Pore structure; Pore-scale characterization; Porous media; Predicting brittleness index; Predicting proximal analysis; Predicting total organic carbon; Prediction accuracy; Proximate analysis; Reserve estimation; Reservoir characterization; Reservoir simulation; Resource uncertainty; Seismic attributes; Shale; Shale gas; Shale properties from well-log data; Subjective weights; Temperature; Thin-section/SEM analysis; Time-temperature integral models; Total organic content; Unconventional gas resources; Variable E-A kinetic models; VBA coded Solver; Well-log sampling density; Well-log variable relationships
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
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
3D modeling; Acoustic impedance; Arrhenius first-order reactions; Brittleness; Carbonate and clastic microfacies; CBM well-log relationships; Climate change; Clustering/classification algorithms; Coal characterization; Coal gas content; Coal structure indices; Coal-bed methane; Coarse-detailed feature extraction; Constant-A kinetic models; Conventional gas resources; Correlation coefficients; Correlation-free prediction analysis; Customized formula optimization; Deep learning; Density; Development assessment protocol; Energy resource; Entropy weights; Error minimization; Established E versus LnA trends for shales; Feature influence; Feature quantification; Few-shot; Fracability; Fractal; Fractal theory; Fuzzy/intuitionistic TOPSIS; Gas adsorption; Gas detection; Gas hydrate; Gas reservoir; Geohazard; Geological model; Geomechanics; Gulf of Suez; Horizontal stress differentials; Hydraulic fracturing; Image arithmetic; Image enhancement; Immature Duvernay shale; Integrated deep learning model; Intelligent logging evaluation; Kerogen transformation processes; Large-field case studies; Machine learning; Machine learning transparency mineralogical and elastic influences; Microseismic geomechanics; Microseismic monitoring; Multicriteria decision analysis (MCDA); Multilinear regression; Multiple-heating rate pyrolysis peak fitting; Nonlinear functions; Organic carbon; Petrographic interpretation; Petroleum generation complexities; Petroleum-generation kinetics; Physical property; Pore pressure prediction; Pore structure; Pore-scale characterization; Porous media; Predicting brittleness index; Predicting proximal analysis; Predicting total organic carbon; Prediction accuracy; Proximate analysis; Reserve estimation; Reservoir characterization; Reservoir simulation; Resource uncertainty; Seismic attributes; Shale; Shale gas; Shale properties from well-log data; Subjective weights; Temperature; Thin-section/SEM analysis; Time-temperature integral models; Total organic content; Unconventional gas resources; Variable E-A kinetic models; VBA coded Solver; Well-log sampling density; Well-log variable relationships
