Sustainable natural gas reservoir and production engineering /

Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Wood, David A. (Petroleum engineer) (Editor ), Cai, Jianchao (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cambridge, MA : Gulf Professional Publishing, [2022]
Colección:Fundamentals and sustainable advances in natural gas science and engineering series ; v. 1.
Temas:
Gas reservoirs.
Production engineering.
R�eservoirs de gaz naturel (G�eologie)
Technique de la production.
Gas reservoirs
Production engineering
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Intro
  • Sustainable Natural Gas Reservoir and Production Engineering
  • Copyright
  • Contents
  • Contributors
  • Preface
  • About the fundamentals and sustainable advances in natural gas science and engineering series
  • About volume 1: sustainable natural gas reservoir and production engineering
  • Chapter One: Gas properties, fundamental equations of state and phase relationships
  • 1. Introduction to natural gas
  • 1.1. Composition of natural gas
  • 1.2. Classification of natural gas
  • 1.3. Measurement standards
  • 2. Gas equation of state
  • 2.1. Equation of state
  • 2.2. Calculation of compressibility factor
  • 3. Physical and thermodynamic properties of natural gas
  • 3.1. Relative molecular mass
  • 3.2. Density of natural gas
  • 3.3. Critical parameters and reduced parameters
  • 3.4. Enthalpy of natural gas
  • 3.5. Entropy of natural gas
  • 3.6. Specific heat capacity of natural gas
  • 3.7. Joule-Thompson coefficient
  • 3.8. Calorific value of natural gas
  • 3.9. Explosion limit of natural gas
  • 3.10. Viscosity of natural gas
  • 3.11. Thermal conductivity coefficient of natural gas
  • 4. Phase relationships of natural gas
  • 4.1. Dew point and bubble point of natural gas
  • 4.2. Vaporization rate of natural gas
  • 5. Summary
  • References
  • Chapter Two: Natural gas demand prediction: Methods, time horizons, geographical scopes, sustainability issues, and scenarios
  • 1. Introduction
  • 2. Fundamentals of natural gas demand prediction requirements
  • 3. Advanced aspects of natural gas demand prediction methodologies
  • 3.1. Identifying relevant published research on gas prediction
  • 3.2. Analysis of gas prediction methodologies applied based on the relevant published research identified
  • 3.2.1. Questions addressed in the analysis
  • 3.2.2. Insight gained from analysis of published gas prediction studies.
  • 3.2.3. Prediction time horizons and geographical scopes
  • 3.2.4. Sustainable development features considered in published studies
  • 4. Case study: A learning scenario development model providing sustainable global natural gas demand predictions
  • 5. Summary
  • A. Appendix
  • References
  • Chapter Three: Machine learning to improve natural gas reservoir simulations
  • 1. Introduction
  • 2. Fundamental concepts and key principles
  • 2.1. Reservoir simulation
  • 2.2. Governing equations of gas reservoir simulations
  • 3. Advanced research/field applications
  • 3.1. Application of ML in data preprocessing and prediction of properties
  • 3.2. Application of ML in governing equations and numerical solutions
  • 3.3. Application of ML in history matching
  • 3.4. Application of ML in proxy modeling and optimization
  • 4. Case study: Dew point prediction for gas condensate reservoirs
  • 4.1. Dew point pressure
  • 4.2. Data analysis
  • 4.3. ANN-TLBO model design
  • 4.4. CNN model design
  • 4.5. Overfitting and appropriate remedies
  • 4.6. Evaluation and discussion
  • 5. Summary
  • Chapter Three. References
  • References
  • Chapter Three. References
  • References
  • Chapter Four: In situ stress and mechanical properties of unconventional gas reservoirs
  • 1. Introduction
  • 2. Fundamental concepts and key principles
  • 2.1. In situ stress
  • 2.2. Mechanical properties of unconventional reservoirs
  • 2.2.1. Calculation of static mechanical parameters
  • 2.2.2. Dynamic mechanical parameters calculation
  • 3. Advanced research/field applications
  • 3.1. Brittleness evaluation index application
  • 3.2. Field applications
  • 4. Case study
  • 4.1. Geological background
  • 4.2. Samples and data processing
  • 4.3. Reservoir characteristics
  • 4.4. Geomechanical parameters
  • 4.4.1. Static mechanical test results
  • 4.4.2. Conversion of dynamic and static parameters.
  • 4.5. Brittleness analysis of shale
  • 4.6. In-situ stress magnitude
  • 5. Summary and conclusions
  • Declarations
  • Chapter Four. References
  • References
  • Chapter Five: Hydraulic fracturing of unconventional reservoirs aided by simulation technologies
  • 1. Introduction
  • 2. Mathematical models for hydraulic fracturing
  • 2.1. Governing equations
  • 2.1.1. Deformation of the rock matrix and the fractures
  • 2.1.2. Fracture propagation
  • 2.1.3. Fluid flow in fractures and pores
  • 2.1.4. Thermal transport
  • 2.2. Analytical and semi-analytical solutions for the propagation of a single hydraulic fracture
  • 3. Numerical methods for simulation of hydraulic fracturing
  • 4. Case study: Simulation of hydraulic fracture propagation in a shale formation
  • 4.1. Model generation
  • 4.2. Effects of 3D stress on induced fracture propagation
  • 4.3. Effects of natural fracture orientations on induced fracture propagation
  • 4.4. Effects of natural fracture state on induced fracture propagation
  • 4.5. Effects of drilling direction on induced fracture propagation
  • 5. Summary and conclusions
  • Chapter Five. References
  • References
  • Chapter Six: Experimental methods in fracturing mechanics focused on minimizing their environmental footprint
  • 1. Introduction
  • 2. Experimental methods in fracturing mechanics
  • 2.1. Micromechanical tests of rock
  • 2.1.1. Grid nanoindentation tests
  • 2.1.2. Atomic force microscope for micromechanical properties mapping
  • SEM and EDS
  • Atomic force microscopy (AFM)
  • High resolution characterization of individual mineral aggregates
  • 2.2. Triaxial tests for rocks with SC-CO2
  • 2.3. Triaxial direct shear test for rocks and shear induced permeability evolution
  • 2.3.1. Experimental setup
  • 2.3.2. Experimental scheme and procedure
  • 2.4. Mechanical test of rock sample treated by liquid nitrogen.
  • 2.4.1. Macro-scale mechanical tests under LN2 freezing condition
  • 2.4.2. Cryo-scanning electron microscopy test
  • 3. Experimental methods for waterless fracturing
  • 3.1. Triaxial fracturing system
  • 3.1.1. True triaxial-loading and heating vessel
  • 3.1.2. Pumping system for supercritical CO2
  • 3.1.3. Pumping system for liquid nitrogen
  • 3.2. Triaxial fracturing for supercritical CO2
  • 3.2.1. Rock specimen preparation
  • 3.2.2. Experimental procedures
  • 3.2.3. Experimental results
  • 3.3. Triaxial fracturing for liquid nitrogen
  • 3.3.1. Experimental procedures
  • 3.3.2. Fracturing experiment results
  • 3.4. High-speed imaging of multiple fract propagation using homogenous transparent solids
  • 3.4.1. Transparent material selection
  • 3.4.2. Modified triaxial vessel and transparent solids for high-speed imaging
  • 3.4.3. Scaling laws and parameter design
  • 3.4.4. Experiment procedures
  • 4. Fracture monitoring and analysis methods
  • 4.1. Manual optical observation method
  • 4.2. Acoustic emission monitoring method
  • 4.3. 2D slice image analysis
  • 4.4. 3D profilometry technique
  • 4.5. 3D CT image reconstruction
  • 4.6. CT images for characterization of fracture parameters
  • 4.7. Other fracture evaluating approach
  • Chapter Six. References
  • References
  • Chapter Seven: Production decline curve analysis and reserves forecasting for conventional and unconventional gas reservoirs
  • 1. Introduction
  • 2. Fundamental concepts and key principles
  • 2.1. Historical decline curve fitting methods
  • 2.2. Arps model
  • 2.3. Rate-cumulative relationships to establish reserves and EUR
  • 2.4. Constraints and assumption applied with Arps models
  • 3. Advanced research/field applications
  • 3.1. Segmented decline curves suited to unconventional reservoirs
  • 3.2. Power law exponential decline (PLE)
  • 3.3. Stretched exponential decline (SEPD).
  • 3.4. Duong's method
  • 3.5. Logistic growth analysis (LGA)
  • 3.6. Fetkovich type curve
  • 3.7. Wattenbarger type curve
  • 3.8. Blasingame type curve
  • 3.9. Agarwal-Gardner type curve
  • 3.10. Normalized pressure integral (NPI)
  • 4. Case studies
  • 4.1. Tip-top field conventional gas/vertical well case
  • 4.2. Unconventional gas/horizontal well
  • 5. Summary
  • References
  • Chapter Eight: Well test analysis for characterizing unconventional gas reservoirs
  • 1. Introduction
  • 2. Reservoir flow regimes
  • 3. Pressure transient analysis (PTA)
  • 3.1. Well test analysis for radial flow regime
  • 3.2. Well test analysis for linear and elliptical flow regimes
  • 3.3. Field example: Well test analysis for a multifractured shale gas reservoir
  • 4. Rate transient analysis (RTA)
  • 4.1. RTA field example: Multifractured shale gas reservoir
  • 5. Uncertainties of SRV characterization using analytical methods
  • 6. Characterizing SRV according to dual-permeability model
  • 7. Effect of multiphase flow on PTA in unconventional Wells
  • 8. A typical example in multiphase producing well test
  • 9. Temperature transient analysis
  • 10. Conclusions
  • References
  • Chapter Nine: Carbon-nanotube-polymer nanocomposites enable wellbore cements to better inhibit gas migration and enhance ...
  • 1. Fundamental concepts
  • 1.1. The key role of cement in achieving well integrity
  • 1.2. Application of polymer additives in wellbore cement
  • 1.3. Application of nanoparticles as wellbore cement additives
  • 1.4. Wellbore cement reinforcement by CNT-polymer nanocomposite additive
  • 2. Advanced consideration in controlling wellbore gas migration
  • 2.1. Potential gas migration occurrences in wellbores
  • 2.2. Major mechanisms in the emergence of gas migration in cement
  • 2.2.1. Cement gelatinization in transient time.

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