Introduction to modeling, simulation and optimization of CO2 sequestration in various types of reservoirs - Agarwal, Ramesh K. 1947-; Liu, Danqing (Elsevier, 2025)
Carbon capture and sequestration has become an essential technology for addressing the mitigation of global warming and adverse climate change due to increasing CO2 emissions from fossil fuel combustion worldwide. However, the scientific/engineering community still lacks thorough and practical knowledge about various types of reservoirs capable of effective long-term CO2 sequestration. Introduction to Modeling, Simulation, and Optimization of CO2 Sequestration in Various Types of Reservoirs pulls together the relevant basic scientific knowledge and applications to help reservoir engineering practitioners learn and utilize the potential of CO2 sequestration in saline, oil, gas, shale, basalt, and geothermal reservoirs. After presenting the fundamental properties of various reservoirs, the authors describe each type of reservoir and explain basic parameters, benchmark cases, experimental data, optimization strategies for CO2 sequestration, prospects, and outlook. Rounding out the text with a glossary and consideration of future developments, this book delivers the necessary tools for engineers to better understand carbon sequestration and advance the energy transition
Preface Acknowledgments Chapter 1 Carbon capture, utilization and storage: technology development and applications, policy considerations and techno-economic analysis Chapter 2 Basic properties of CO2, ground water and geological storage sites Chapter 3 Numerical methods and codes used in CCUS simulation and optimization Chapter 4 Geological sequestration of CO2 in deep saline aquifers Chapter 5 CO2 sequestration in basaltic reservoir Chapter 6 CO2 Enhanced Oil Recovery(CO2-EOR) Chapter 7 CO2 Enhanced Gas Recovery(CO2-EGR) Chapter 8 CO2 Enhanced Geothermal System Recovery(CO2-EGS) Chapter 9 CO2 Enhanced Shale Gas Recovery(CO2-ESGR) Chapter 10 CO2 Enhanced Water Recovery(CO2-EWR) Chapter 11 Application of machine learning in CCUS
Keywords: bisacsh