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Improving predictions of shale wettability using advanced machine learning techniques and nature-inspired methods: Implications for carbon capture utilization and storage.
Zhang, Hemeng; Thanh, Hung Vo; Rahimi, Mohammad; Al-Mudhafar, Watheq J; Tangparitkul, Suparit; Zhang, Tao; Dai, Zhenxue; Ashraf, Umar.
Afiliação
  • Zhang H; College of Safety Science and Engineering, Liaoning Technical University, Huludao 125105, China; Key Laboratory of Mine Thermodynamic Disasters and Control of Ministry of Education, Huludao 125105, China. Electronic address: zhanghemeng@lntu.edu.cn.
  • Thanh HV; Laboratory for Computational Mechanics, Institute for Computational Science and Artificial Intelligence, Van Lang University, Ho Chi Minh City, Viet Nam; Faculty of Mechanical-Electrical and Computer Engineering, School of Technology, Van Lang University, Ho Chi Minh City, Viet Nam. Electronic addre
  • Rahimi M; Department of Biosystems Engineering, Ferdowsi University of Mashhad, Mashhad, Iran.
  • Al-Mudhafar WJ; Basrah Oil Company, Iraq.
  • Tangparitkul S; Department of Mining and Petroleum Engineering, Chiang Mai University, Thailand.
  • Zhang T; State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University, Chendu, China.
  • Dai Z; School of Environmental and Municipal Engineering, Qingdao University of Technology, Qingdao 266520, China; College of Construction Engineering, Jilin University, Changchun, China.
  • Ashraf U; Institute for Ecological Research and Pollution Control of Plateau Lakes, School of Ecology and Environmental Science, Yunnan University, Kunming 650504, China.
Sci Total Environ ; 877: 162944, 2023 Jun 15.
Article em En | MEDLINE | ID: mdl-36940746
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article
Texto completo
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article