Bicheng Yan

3.1k total citations · 1 hit paper
172 papers, 2.3k citations indexed

About

Bicheng Yan is a scholar working on Ocean Engineering, Mechanical Engineering and Mechanics of Materials. According to data from OpenAlex, Bicheng Yan has authored 172 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 106 papers in Ocean Engineering, 92 papers in Mechanical Engineering and 59 papers in Mechanics of Materials. Recurrent topics in Bicheng Yan's work include Hydraulic Fracturing and Reservoir Analysis (90 papers), Enhanced Oil Recovery Techniques (60 papers) and Reservoir Engineering and Simulation Methods (59 papers). Bicheng Yan is often cited by papers focused on Hydraulic Fracturing and Reservoir Analysis (90 papers), Enhanced Oil Recovery Techniques (60 papers) and Reservoir Engineering and Simulation Methods (59 papers). Bicheng Yan collaborates with scholars based in Saudi Arabia, United States and China. Bicheng Yan's co-authors include John Killough, Yuhe Wang, D. R. Harp, Rajesh Pawar, Shuyu Sun, Masoud Alfi, Zeeshan Tariq, Cheng An, Bailian Chen and Hussein Hoteit and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Journal of Physical Chemistry B and Scientific Reports.

In The Last Decade

Bicheng Yan

145 papers receiving 2.2k citations

Hit Papers

Artificial intelligence-based prediction of hydrogen adso... 2024 2026 2025 2024 10 20 30 40

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Bicheng Yan Saudi Arabia 27 1.3k 1.2k 909 541 247 172 2.3k
Xia Yan China 21 833 0.6× 865 0.7× 603 0.7× 370 0.7× 127 0.5× 90 1.7k
Mohsen Masihi Iran 32 2.6k 2.0× 1.5k 1.2× 1.7k 1.9× 559 1.0× 196 0.8× 178 3.4k
Jihoon Kim United States 21 555 0.4× 793 0.6× 842 0.9× 445 0.8× 372 1.5× 82 2.0k
Zeeshan Tariq Saudi Arabia 28 2.1k 1.6× 1.8k 1.4× 928 1.0× 403 0.7× 242 1.0× 199 3.0k
Lei Li China 29 1.7k 1.3× 1.2k 1.0× 1.4k 1.5× 470 0.9× 53 0.2× 145 2.5k
Xiaoliang Zhao China 23 801 0.6× 789 0.6× 382 0.4× 327 0.6× 96 0.4× 95 1.7k
Yongming Li China 23 892 0.7× 951 0.8× 588 0.6× 181 0.3× 157 0.6× 85 1.7k
Stephen Butt Canada 27 1.6k 1.2× 1.2k 1.0× 688 0.8× 128 0.2× 316 1.3× 162 2.4k
Liang Luo China 19 421 0.3× 824 0.7× 450 0.5× 331 0.6× 56 0.2× 41 1.8k
Hui Zhao China 24 1.2k 0.9× 1.1k 0.9× 419 0.5× 136 0.3× 65 0.3× 115 1.7k

Countries citing papers authored by Bicheng Yan

Since Specialization
Citations

This map shows the geographic impact of Bicheng Yan'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 Bicheng Yan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bicheng Yan more than expected).

Fields of papers citing papers by Bicheng Yan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bicheng Yan. 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 Bicheng Yan. The network helps show where Bicheng Yan may publish in the future.

Co-authorship network of co-authors of Bicheng Yan

This figure shows the co-authorship network connecting the top 25 collaborators of Bicheng Yan. A scholar is included among the top collaborators of Bicheng Yan 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 Bicheng Yan. Bicheng Yan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Yan, Bicheng, et al.. (2025). A hybrid CNN-transformer surrogate model for the multi-objective robust optimization of geological carbon sequestration. Advances in Water Resources. 196. 104897–104897. 5 indexed citations
2.
Yao, Xinyu, et al.. (2025). Interfacial properties of the hydrogen+brine system in the presence of hydrophilic silica. International Journal of Hydrogen Energy. 101. 741–749. 9 indexed citations
3.
Yao, Xinyu, et al.. (2025). Molecular Dynamics Simulations of Interfacial Tensions and Contact Angles of the Nitrogen+Oil+Brine+Rock System. Industrial & Engineering Chemistry Research. 64(7). 3831–3840.
5.
Tariq, Zeeshan, Zhong Zhang, Peilin Zhao, et al.. (2025). CoSwinNet: A conditional Swin Transformer multimodal surrogate model for subsurface multiphase flow. Fuel. 411. 138067–138067.
6.
Yan, Bicheng, et al.. (2024). Physics-informed machine learning for reservoir management of enhanced geothermal systems. Geoenergy Science and Engineering. 234. 212663–212663. 15 indexed citations
7.
Yan, Bicheng, et al.. (2024). On the feasibility of an ensemble multi-fidelity neural network for fast data assimilation for subsurface flow in porous media. Expert Systems with Applications. 264. 125774–125774. 1 indexed citations
8.
Gudala, Manojkumar, Bicheng Yan, Zeeshan Tariq, Fengshou Zhang, & Shuyu Sun. (2024). Doublet huff and puff: A new technology for efficient geological CO2 sequestration and stable geothermal recovery. Applied Energy. 367. 123349–123349. 4 indexed citations
9.
Guo, Zhaoli, et al.. (2024). Implementation of contact line motion based on the phase-field lattice Boltzmann method. Physical review. E. 109(4). 45307–45307. 3 indexed citations
10.
Yan, Bicheng, et al.. (2024). A Novel Hybrid Physics/Data-Driven Model for Fractured Reservoir Simulation. SPE Journal. 29(12). 7029–7045. 4 indexed citations
11.
Zhang, Hongwei, Xin Wang, Qinjun Kang, et al.. (2023). Transport properties of oil-CO2 mixtures in calcite nanopores: Physics and machine learning models. Fuel. 358. 130308–130308. 3 indexed citations
12.
Yan, Bicheng, et al.. (2023). Data driven approach using capacitance resistance model to determine polymer in-situ retention level. Geoenergy Science and Engineering. 229. 212043–212043. 2 indexed citations
13.
Yan, Bicheng, Manojkumar Gudala, & Shuyu Sun. (2023). Robust optimization of geothermal recovery based on a generalized thermal decline model and deep learning. Energy Conversion and Management. 286. 117033–117033. 18 indexed citations
14.
Moridis, George J., et al.. (2023). Compositional reservoir simulation of underground hydrogen storage in depleted gas reservoirs. International Journal of Hydrogen Energy. 48(92). 36035–36050. 67 indexed citations
15.
Tariq, Zeeshan, Manojkumar Gudala, Bicheng Yan, Shuyu Sun, & Mohamed Mahmoud. (2023). A fast method to infer Nuclear Magnetic Resonance based effective porosity in carbonate rocks using machine learning techniques. Geoenergy Science and Engineering. 222. 211333–211333. 15 indexed citations
16.
Tariq, Zeeshan, et al.. (2023). Enhancing Fracturing Fluid Viscosity in High Salinity Water: A Data-Driven Approach for Prediction and Optimization. Energy & Fuels. 37(17). 13065–13079. 7 indexed citations
17.
Tariq, Zeeshan, Bicheng Yan, Shuyu Sun, et al.. (2022). Machine Learning-Based Accelerated Approaches to Infer Breakdown Pressure of Several Unconventional Rock Types. ACS Omega. 7(45). 41314–41330. 5 indexed citations
18.
Yan, Bicheng, Yuhe Wang, & John Killough. (2015). Beyond dual-porosity modeling for the simulation of complex flow mechanisms in shale reservoirs. Computational Geosciences. 20(1). 69–91. 111 indexed citations
19.
Yan, Bicheng, Masoud Alfi, Yuhe Wang, & John Killough. (2013). A New Approach for the Simulation of Fluid Flow in Unconventional Reservoirs through Multiple Permeability Modeling. SPE Annual Technical Conference and Exhibition. 49 indexed citations
20.
Wang, Yuhe, Bicheng Yan, & John Killough. (2013). Compositional Modeling of Tight Oil Using Dynamic Nanopore Properties. SPE Annual Technical Conference and Exhibition. 84 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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