Recent Advances in Geological Storage: Trapping Mechanisms, Storage Sites, Projects, and Application of Machine Learning

Abstract

A significant amount of carbon dioxide (CO 2 ) 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 CO 2 storage projects, there is still not enough to moderate global temperatures. Therefore, there is an urgent need for the development of CO 2 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 CO 2 sequestration is reviewed toward the end. This extensive review reveals that the main variables affecting CO 2 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.