Prediction of CO2 storage site integrity with rough set-based machine learning

• Main Authors: Aviso, Kathleen B., Janairo, Jose Isagani B., Promentilla, Michael Angelo B., Tan, Raymond Girard R.
• Format: text
• Published: Animo Repository 2019
• Subjects: Carbon sequestration; Artificial intelligence; Chemical Engineering
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/1871; https://animorepository.dlsu.edu.ph/context/faculty_research/article/2870/type/native/viewcontent
• Institution: De La Salle University

CO2 capture and storage (CCS) and negative emissions technologies (NETs) are considered to be essential carbon management strategies to safely stabilize climate. CCS entails capture of CO2 from combustion products from industrial plants and subsequent storage of this CO2 in geological formations or...