Ming Fan

1.1k total citations
63 papers, 821 citations indexed

About

Ming Fan is a scholar working on Mechanics of Materials, Ocean Engineering and Mechanical Engineering. According to data from OpenAlex, Ming Fan has authored 63 papers receiving a total of 821 indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Mechanics of Materials, 23 papers in Ocean Engineering and 21 papers in Mechanical Engineering. Recurrent topics in Ming Fan's work include Hydrocarbon exploration and reservoir analysis (22 papers), Hydraulic Fracturing and Reservoir Analysis (19 papers) and Lattice Boltzmann Simulation Studies (12 papers). Ming Fan is often cited by papers focused on Hydrocarbon exploration and reservoir analysis (22 papers), Hydraulic Fracturing and Reservoir Analysis (19 papers) and Lattice Boltzmann Simulation Studies (12 papers). Ming Fan collaborates with scholars based in United States, China and Australia. Ming Fan's co-authors include Cheng Chen, James E. McClure, Yanhui Han, Dustin Crandall, Laura E. Dalton, Dan Lu, Nino Ripepi, Erik Westman, Siyan Liu and Zhongmin Xiao and has published in prestigious journals such as Geophysical Research Letters, Journal of Hydrology and Construction and Building Materials.

In The Last Decade

Ming Fan

62 papers receiving 804 citations

Peers

Ming Fan

Jens-Oliver Schwarz Germany

Rudolf Held Norway

Rosalind Archer New Zealand

Hai Huang United States

Yi Jin China

Mian Lin China

Florian Doster United Kingdom

L. Leu Netherlands

Xiaojing Fu United States

Jeremy Jameson Germany

Jens-Oliver Schwarz Germany

Ming Fan

578 ×1.5

536 ×1.5

347 ×1.0

282 ×1.4

144 ×1.4

Citations per year, relative to Ming Fan Ming Fan (= 1×) peers Jens-Oliver Schwarz

Countries citing papers authored by Ming Fan

Since Specialization

Citations

This map shows the geographic impact of Ming Fan's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ming Fan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ming Fan more than expected).

Fields of papers citing papers by Ming Fan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ming Fan. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ming Fan. The network helps show where Ming Fan may publish in the future.

Co-authorship network of co-authors of Ming Fan

This figure shows the co-authorship network connecting the top 25 collaborators of Ming Fan. A scholar is included among the top collaborators of Ming Fan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ming Fan. Ming Fan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Wang, Xiao, Jong Youl Choi, Hong‐Jun Yoon, et al.. (2025). ORBIT-2: Scaling Exascale Vision Foundation Models for Weather and Climate Downscaling. 86–98. 1 indexed citations

Zhang, Lujun, Tiantian Yang, Shang Gao, et al.. (2025). An Alternative Ensemble Streamflow Prediction Approach Using Improved Subseasonal Precipitation Forecasts from the North America Multi-Model Ensemble Phase II. Journal of Hydrometeorology. 26(3). 309–326. 2 indexed citations

Yuan, Yueyi, et al.. (2025). Deformable Perfect Vortex Wave-Front Modulation Based on Geometric Metasurface in Microwave Regime. Chinese Journal of Electronics. 34(1). 64–72. 7 indexed citations

Fan, Ming, Zezhong Zhang, Dan Lu, & Guannan Zhang. (2025). GenAI4UQ: A software for forward and inverse uncertainty quantification using conditional generative AI. SoftwareX. 31. 102232–102232. 2 indexed citations

Fan, Ming, Dan Lu, & Sudershan Gangrade. (2025). Enhancing Multi-Step Reservoir Inflow Forecasting: A Time-Variant Encoder–Decoder Approach. Geosciences. 15(8). 279–279. 3 indexed citations

Wang, Hongsheng, et al.. (2024). A deep learning-based workflow for fast prediction of 3D state variables in geological carbon storage: A dimension reduction approach. Journal of Hydrology. 636. 131219–131219. 10 indexed citations

Han, Yuanjia, Hanyong Bao, Ming Fan, et al.. (2024). On the generation of light hydrocarbons from the closed pores of Jurassic strata, Sichuan Basin. Marine and Petroleum Geology. 171. 107208–107208.

Fan, Ming, et al.. (2024). A novel conditional generative model for efficient ensemble forecasts of state variables in large-scale geological carbon storage. Journal of Hydrology. 648. 132323–132323. 3 indexed citations

Fan, Ming, et al.. (2024). Advancing spatiotemporal forecasts of CO2 plume migration using deep learning networks with transfer learning and interpretation analysis. International journal of greenhouse gas control. 132. 104061–104061. 8 indexed citations

10.

Liu, Siyan, Ming Fan, & Dan Lu. (2023). Uncertainty quantification of the convolutional neural networks on permeability estimation from micro-CT scanned sandstone and carbonate rock images. Geoenergy Science and Engineering. 230. 212160–212160. 6 indexed citations

11.

Fan, Ming, Lujun Zhang, Siyan Liu, Tiantian Yang, & Dan Lu. (2023). Investigation of hydrometeorological influences on reservoir releases using explainable machine learning methods. Frontiers in Water. 5. 13 indexed citations

12.

Lu, Xiancai, et al.. (2023). Breakthrough Pressure Model of Shale Gas in Water-Saturated Nanopore-Throat Systems: Insights from Molecular Simulations. Transport in Porous Media. 150(3). 735–752. 4 indexed citations

13.

Yu, Lingjie, et al.. (2022). Estimating Lost Gas Content for Shales Considering Real Boundary Conditions during the Core Recovery Process. ACS Omega. 7(24). 21246–21254. 5 indexed citations

14.

McClure, James E., Ming Fan, Steffen Berg, et al.. (2022). Relative permeability as a stationary process: energy fluctuations in immiscible displacement. arXiv (Cornell University). 24 indexed citations

15.

Fan, Ming, Lujun Zhang, Siyan Liu, Tiantian Yang, & Dan Lu. (2022). Identifying Hydrometeorological Factors Influencing Reservoir Releases Using Machine Learning Methods. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 1102–1110. 5 indexed citations

16.

Yu, Lingjie, Ming Fan, Tianyu Chen, et al.. (2021). Two-Phase Flow Model for Numerical Investigation of Impact of Water Retention on Shale Gas Production. Geofluids. 2021. 1–17. 4 indexed citations

17.

Fan, Ming, Yanhui Han, Ming Gu, et al.. (2019). Combining Discrete Element Method with Lattice Boltzmann Modeling to Advance the Understanding of the Performance of Proppant Mixtures. 53rd U.S. Rock Mechanics/Geomechanics Symposium. 3 indexed citations

18.

Fan, Ming, et al.. (2018). Investigating the Impact of Proppant Embedment and Compaction on Fracture Conductivity Using a Continuum Mechanics, DEM, and LBM Coupled Approach. 52nd U.S. Rock Mechanics/Geomechanics Symposium. 5 indexed citations

19.

Fan, Ming, et al.. (2016). Interaction between Proppant Packing, Reservoir Depletion, and Fluid Flow in Pore Space. AGU Fall Meeting Abstracts. 2016. 1 indexed citations

20.

Li, Zhiming, Changjiang Zhang, Jianzhong Qin, et al.. (2007). Geochemical characteristics of crude oils from Well Zheng-1 in the Junggar Basin, Xinjiang, China. Geochemistry. 26(2). 163–169. 4 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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