Sustainable Geoscience for Natural Gas SubSurface Systems

Sustainable Geoscience for Natural Gas SubSurface Systems

1st Edition - October 30, 2021

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  • Editors: David Wood, Jianchao Cai
  • Paperback ISBN: 9780323854658
  • eBook ISBN: 9780323854665

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Description

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.

Key Features

  • 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

Readership

Natural gas engineers; reservoir engineers; geoscience engineers; petrophysicists. Carbon management researchers

Table of Contents

  • Cover image
  • Title page
  • Table of Contents
  • Copyright
  • Contributors
  • Preface
  • About The Fundamentals and Sustainable Advances in Natural Gas Science and Engineering Series
  • About this volume 2: Sustainable geoscience for natural gas subsurface systems
  • Chapter One: Pore-scale characterization and fractal analysis for gas migration mechanisms in shale gas reservoirs
  • Abstract
  • Acknowledgments
  • 1: Introduction
  • 2: Pore-scale characterization from nitrogen adsorption-desorption data
  • 3: Pore-scale characterization from SEM data
  • 4: Definitions of fractal parameters
  • 5: Fractal analysis of nitrogen adsorption isotherms
  • 6: Fractal analysis of SEM images
  • 7: Pore-scale and core-scale gas transport mechanisms
  • 8: Conclusions
  • References
  • Chapter Two: Three-dimensional gas property geological modeling and simulation
  • Abstract
  • 1: Introduction
  • 2: 3D modeling
  • 3: Geological conditions of gas reservoirs
  • 4: Typical earth data used in modeling
  • 5: Modeling methods
  • 6: Structural modeling
  • 7: Facies modeling
  • 8: Petrophysical modeling
  • 9: Geomechanical modeling
  • 10: Volumetric modeling
  • 11: Case study
  • 12: 3D structural modeling
  • 13: 3D facies modeling
  • 14: 3D petrophysical modeling
  • 15: 3D geomechanical modeling
  • 16: Summary
  • References
  • Chapter Three: Acoustic, density, and seismic attribute analysis to aid gas detection and delineation of reservoir properties
  • Banner headline
  • 1: Introduction
  • 2: Natural gas reservoirs detection
  • 3: Delineation and characterization of natural gas reservoirs
  • 4: Summary
  • References
  • Chapter Four: Integrated microfacies interpretations of large natural gas reservoirs combining qualitative and quantitative image analysis
  • Abstract
  • Declarations
  • 1: Introduction
  • 2: Fundamental concepts and key principles
  • 3: Advanced research and detailed techniques
  • 4: Gas field case studies
  • 5: Summary
  • References
  • Chapter Five: Assessing the brittleness and total organic carbon of shale formations and their role in identifying optimum zones to fracture stimulate
  • Abstract
  • Declarations
  • 1: Introduction
  • 2: Fundamental concepts
  • 3: Advanced methods
  • 4: Case study: TOB machine learning to predict shale brittleness and TOC
  • 5: Summary
  • References
  • Chapter Six: Shale kerogen kinetics from multiheating rate pyrolysis modeling with geological time-scale perspectives for petroleum generation
  • Abstract
  • 1: Fundamental concepts
  • 2: Advanced techniques and applications
  • 3: Case study kinetic models for immature Duvernay shale Western Canada
  • 4: Summary
  • References
  • Chapter Seven: Application of few-shot semisupervised deep learning in organic matter content logging evaluation
  • Abstract
  • Acknowledgment
  • 1: Introduction
  • 2: Methodology
  • 3: Samples and experiments
  • 4: Results: TOC Prediction comparisons for IDLM and other models
  • 5: Conclusions
  • References
  • Chapter Eight: Microseismic analysis to aid gas reservoir characterization
  • Abstract
  • Acknowledgments
  • 1: Introduction
  • 2: Principle and workflow of microseismic monitoring
  • 3: Advanced processing and interpretation techniques
  • 4: Case studies
  • 5: Summary
  • References
  • Chapter Nine: Coal-bed methane reservoir characterization using well-log data
  • Abstract
  • 1: Introduction
  • 2: Fundamental concepts pertaining to CBM
  • 3: Advanced assessment of coal bed methane properties
  • 4: Case study: Assessing coal fracability based on well-log information
  • 5: Summary
  • References
  • Chapter Ten: Characterization of gas hydrate reservoirs using well logs and X-ray CT scanning as resources and environmental hazards
  • Banner Headline
  • Acknowledgments
  • 1: Introduction
  • 2: Fundamental concepts and key principles
  • 3: Advanced research/field applications
  • 4: Case studies
  • 5: Summary and conclusions
  • References
  • Chapter Eleven: Assessing the sustainability of potential gas hydrate exploitation projects by integrating commercial, environmental, social and technical considerations
  • Abstract
  • Declarations
  • 1: Fundamental concepts
  • 2: Advanced TOPSIS techniques that incorporate uncertainty
  • 3: Case study
  • 4: Suggested protocol and MCDA analysis for large resource development projects
  • 5: Summary
  • References
  • Chapter Twelve: Gas adsorption and reserve estimation for conventional and unconventional gas resources
  • Abstract
  • 1: Introduction
  • 2: Reserves estimations for gas-bearing reservoirs
  • 3: Material balance equation and gas adsorption in conventional and unconventional reservoirs
  • 4: Gas adsorption/desorption isotherms
  • 5: Estimating gas reserves for coal bed methane resources
  • 6: Gas adsorption considerations relevant to unconventional gas resources and reserves estimation
  • 7: Case study examples for estimating gas resources (GIIP) and reserves
  • 8: Summary
  • References
  • Chapter Thirteen: Dataset insight and variable influences established using correlations, regressions, and transparent customized formula optimization
  • Abstract
  • 1: Introduction
  • 2: Fundamental concepts
  • 3: Advanced considerations
  • 4: Case study
  • 5: Summary
  • References
  • Index

Product details

  • No. of pages: 434
  • Language: English
  • Copyright: © Gulf Professional Publishing 2021
  • Published: October 30, 2021
  • Imprint: Gulf Professional Publishing
  • Paperback ISBN: 9780323854658
  • eBook ISBN: 9780323854665

About the Editors

David Wood

Dr. David Wood has more than forty years of international oil and gas experience spanning technical and commercial exploration and production operations, midstream and downstream projects, contract evaluation and senior corporate management. For the past two decades, David has worked as an independent international consultant, researcher, training provider and expert witness. He has published an extensive body of work including some 350 publications and four books. He frequently acts as an advisor and/or trainer to governments and companies on many technical and commercial aspects of the oil and gas industry through his consultancy, DWA Energy Limited. He has extensive editorial experience as a founding editor of Elsevier’s Journal of Natural Gas Science & Engineering in 2008/9 then serving as Editor-in-Chief for that journal from 2013 to 2016. David obtained his PhD from Imperial College, London (U.K.) and worked as a post-doctoral research fellow in the Institute de Physique du Globe (Paris, France) and Birmingham University (U.K.).

Affiliations and Expertise

Owner/Consultant, DWA Energy Limited, UK

Jianchao Cai

Jianchao Cai received his B.Sc in Physics from Henan Normal University and MSc and Ph.D in Condensed Matter Physics from Huazhong University of Science and Technology. He is currently a professor at the Institute of Geophysics and Geomatics at the China University of Geosciences (Wuhan). Meanwhile, he serves as Associate Editor or Editorial member for several journals including Journal of Natural Gas Science & Engineering, International Journal of Oil, Gas and Coal Technology, Fractals. He has published more than 130 journal articles, two books, and numerous book chapters.

Affiliations and Expertise

Professor, Institute of Geophysics and Geomatics, China University of Geosciences, Wuhan, Hubei, China

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