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CHANG Haibin

Date:2024-06-28 Click:

Haibin Chang received bachelor’s degree in mechanics from Jilin University, China, and received PhD degree in energy and resources engineering from Peking University, China. After that he sequentially worked as post doctor and research scientist in Peking University. He joined China University of Mining and Technology (Beijing) in June 2022. His research interests include subsurface flow simulation, production optimization, data assimilation, machine learning, and underground gas storage. He published over 20 journal papers, which are published in high quality journals, such as《Journal of Computational Physics》,《Computer Methods in Applied Mechanics and Engineering》,《Journal of Geophysical Research: Solid Earth》,《SPE Journal》and《Water Resources Research》.His 10 representative papers are listed below.

[1] Wang, N., Chang, H. *, Zhang, D. *, Efficient uncertainty quantification for dynamic subsurface flow with surrogate by Theory-guided Neural Network. Computer Methods in Applied Mechanics and Engineering. 2021, 373, 113492.

[2] Wang, N., Chang, H. *, Zhang, D. *, Deep-Learning-Based Inverse Modeling Approaches: A Subsurface Flow Example. Journal of Geophysical Research: Solid Earth. 2021, 126(2), e2020JB020549.

[3]Xu, H., Chang, H. *, Zhang, D.*, DLGA-PDE: Discovery of PDEs with incomplete candidate library via combination of deep learning and genetic algorithm. Journal of Computational Physics. 2020, 584, 124700.

[4]Chang, H., Zhang, D., Machine learning subsurface flow equations from data. Computational Geosciences. 2019, 23(5), 895-910.

[5]Chang, H., Zhang, D., Identification of physical processes via combined data-driven and data-assimilation methods. Journal of Computational Physics. 2019, 393, 337-350.

[6]Chang, H., Zhang, D., History matching of stimulated reservoir volume of shale gas reservoirs using an iterative ensemble smoother. SPE Journal. 2018, 23(2), 346 - 366.

[7]Chang, H., Liao, Q., Zhang, D., Surrogate model based iterative ensemble smoother for subsurface flow data assimilation. Advances in Water Resources. 2017, 100, 96-108.

[8]Chang, H., Liao, Q., Zhang, D., Benchmark problems for subsurface flow uncertainty quantification. Journal of Hydrology. 2015, 531, 168-186.

[9]Chang, H., Zhang, D., Lu, Z., History matching of facies distribution with the EnKF and level set parameterization. Journal of Computational Physics. 2010, 229, 8011-8030.

[10]Chang, H., Chen, Y., Zhang, D., Data Assimilation of Coupled Fluid Flow and Geomechanics Using the Ensemble Kalman Filter. SPE Journal. 2010, 15(2), 382-394.

Contact: Haibin Chang

School of Energy and Mining Engineering

China University of Mining and Technology (Beijing)

Ding 11 Xueyuan Road, Beijing 100083, P. R. China

Email: changhaibin@cumtb.edu.cn


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