A significant amount of carbon dioxide (CO2) is being
released into the atmosphere as a result of the acceleration of industrialization
and increased energy consumption, which are causing a rise in world
temperatures. Despite the fact that nations all over the world have
actively participated in CO2 storage projects, there is
still not enough to moderate global temperatures. Therefore, there
is an urgent need for the development of CO2 sequestration
technologies. The main geological storage trapping mechanisms are
discussed in this work along with an analysis of the major influencing
variables. Additionally, the benefits and drawbacks of significant
storage locations and current research hotspots are explored. Storage
project development across the globe is outlined. The use of machine
learning for CO2 sequestration is reviewed toward the end.
This extensive review reveals that the main variables affecting CO2 capture capacity are hydrodynamic and geochemical. The sequestration
capability of various storage sites is significantly influenced by
the reservoir characteristics and implementation methodologies. The
successful implementation of the storage project is determined by
local policies and public support. The development of machine learning
technologies makes storage projects safer and more dependable.