Sustainable Geoscience for Natural Gas SubSurface Systems delivers many of the scientific fundamentals needed in the natural gas industry, including coal-seam gas reservoir characterization and fracture analysis modeling for shale and tight gas reservoirs. Advanced research includes machine learning applications for well log and facies analysis, 3D gas property geological modeling, and X-ray CT scanning to reduce environmental hazards. Supported by corporate and academic contributors, along with two well-distinguished editors, the book gives today’s natural gas engineers both fundamentals and advances in a convenient resource, with a zero-carbon future in mind.
1. Sustainable Geoscience for Natural Gas SubSurface Systems - p. i 2. Cover - p. i 3. Title Page - p. i 4. Copyright Page - p. iv 5. Table of Contents - p. iv 6. Contributors - p. ix 7. Preface - p. xi 8. Chapter One Pore-scale characterization and fractal analysis for gas migration mechanisms in shale gas reservoirs - p. 1 9. Chapter Two Three-dimensional gas property geological modeling and simulation - p. 29 10. Chapter Three Acoustic, density, and seismic attribute analysis to aid gas detection and delineation of reservoir properties - p. 51 11. Chapter Four Integrated microfacies interpretations of large natural gas reservoirs combining qualitative and quantitative image analysis - p. 93 12. Chapter Five Assessing the brittleness and total organic carbon of shale formations and their role in identifying optimum zones to fracture stimulate - p. 129 13. Chapter Six Shale kerogen kinetics from multiheating rate pyrolysis modeling with geological time-scale perspectives for petroleum generation - p. 159 14. Chapter Seven Application of few-shot semisupervised deep learning in organic matter content logging evaluation - p. 197 15. Chapter Eight Microseismic analysis to aid gas reservoir characterization - p. 219 16. Chapter Nine Coal-bed methane reservoir characterization using well-log data - p. 243 17. Chapter Ten Characterization of gas hydrate reservoirs using well logs and X-ray CT scanning as resources and environmental hazards - p. 275 18. Chapter Eleven Assessing the sustainability of potential gas hydrate exploitation projects by integrating commercial, environmental, social and technical considerations - p. 301 19. Chapter Twelve Gas adsorption and reserve estimation for conventional and unconventional gas resources - p. 345 20. Chapter Thirteen Dataset insight and variable influences established using correlations, regressions, and transparent customized formula optimization - p. 383 21. Index - p. 409
Sustainable Geoscience for Natural Gas SubSurface Systems delivers many of the scientific fundamentals needed in the natural gas industry, including coal-seam gas reservoir characterization and fracture analysis modeling for shale and tight gas reservoirs. Advanced research includes machine learning applications for well log and facies analysis, 3D gas property geological modeling, and X-ray CT scanning to reduce environmental hazards. Supported by corporate and academic contributors, along with two well-distinguished editors, the book gives today’s natural gas engineers both fundamentals and advances in a convenient resource, with a zero-carbon future in mind.
1. Sustainable Geoscience for Natural Gas SubSurface Systems - p. i 2. Cover - p. i 3. Title Page - p. i 4. Copyright Page - p. iv 5. Table of Contents - p. iv 6. Contributors - p. ix 7. Preface - p. xi 8. Chapter One Pore-scale characterization and fractal analysis for gas migration mechanisms in shale gas reservoirs - p. 1 9. Chapter Two Three-dimensional gas property geological modeling and simulation - p. 29 10. Chapter Three Acoustic, density, and seismic attribute analysis to aid gas detection and delineation of reservoir properties - p. 51 11. Chapter Four Integrated microfacies interpretations of large natural gas reservoirs combining qualitative and quantitative image analysis - p. 93 12. Chapter Five Assessing the brittleness and total organic carbon of shale formations and their role in identifying optimum zones to fracture stimulate - p. 129 13. Chapter Six Shale kerogen kinetics from multiheating rate pyrolysis modeling with geological time-scale perspectives for petroleum generation - p. 159 14. Chapter Seven Application of few-shot semisupervised deep learning in organic matter content logging evaluation - p. 197 15. Chapter Eight Microseismic analysis to aid gas reservoir characterization - p. 219 16. Chapter Nine Coal-bed methane reservoir characterization using well-log data - p. 243 17. Chapter Ten Characterization of gas hydrate reservoirs using well logs and X-ray CT scanning as resources and environmental hazards - p. 275 18. Chapter Eleven Assessing the sustainability of potential gas hydrate exploitation projects by integrating commercial, environmental, social and technical considerations - p. 301 19. Chapter Twelve Gas adsorption and reserve estimation for conventional and unconventional gas resources - p. 345 20. Chapter Thirteen Dataset insight and variable influences established using correlations, regressions, and transparent customized formula optimization - p. 383 21. Index - p. 409
