Machine Learning-Based Research on Reserve Prediction of Natural-Gas-Hydrates

Author:

Ye Sumin1ORCID,Mai Shuxian1ORCID,Niu Wenbo1ORCID,Yang Tao1ORCID,Ye Lei1ORCID,Zhang Kun2ORCID,Tang Huimin3ORCID,Li Chenglong4ORCID,Peng Boyang5ORCID,Yu Qiannan1ORCID

Affiliation:

1. College of Energy and Power Engineering, Guangdong University of Petrochemical Technology, China

2. School of mechanical sctence and Engineering, Northeast Petroleum University, China and College of Energy and Power Engineering, Guangdong University of Petrochemical Technology, China

3. Hainan Branch CNOOC (China) Co., Ltd., China

4. Exploration and Development Research institute, Daqing Oilfield Co. Ltd., China and Heilongjiang Key Laboratory of Reservoir Physics and Fluid Mechanics in Porous Medium, China

5. Geological Research Institute, No. 4 Oil Production Plant of Daqing Oilfield Co. Ltd., China

Funder

Foundation for Young Talents in Higher Education of Guangdong, China

Maoming Municipal Science and Technology Project

Major Projects of National Science and Technology

Publisher

ACM

Reference15 articles.

1. Research Progress on Oil and Gas Resource Evaluation Methods and New Generation Evaluation Software System;Guo Qiulin;Acta Petrolei Sinica.,2015

2. Eymold W. K. Frederick J. M. Nole M. Phrampus B. J. & Wood W. T. 2021. Prediction of gas hydrate formation at Blake Ridge using machine learning and probabilistic reservoir simulation. Geochemistry Geophysics Geosystems 22(4) e2020GC009574.

3. Comparison of Machine Learning Algorithms for Sand Production Prediction: An Example for a Gas-Hydrate-Bearing Sand Case

4. Research Progress on the Formation Mechanism and Reservoir Prediction of Submarine Sandstone Hydrates;Liu Dejun;Journal of Petrochemical Universities.,2021

5. Qi Lipeng. 2020. Research on the Formation Mechanism and Reservoir Prediction of Submarine Sandstone-Type Hydrates. Liaoning University of Petroleum and Chemical Technology.

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