Bicheng Yan

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Research Interests

Professor Yan's current research interests are physics-driven modeling and data-driven modeling for complex subsurface processes related to energy and environmental domains. He has worked in areas including reservoir simulation, multi-porosity modeling for flow and transport in heterogeneous porous media (mainly shale), integrating physics with data analytics in unconventional field and carbon storage management, history matching and stochastic optimization.

Education

Petroleum Engineering, Ph.D. , Texas A&M University

2017

Petroleum Engineering, M.S. , Texas A&M University

2013

Petroleum Engineering, B.S. , China University of Petroleum - Beijing

2009

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1 Similar Profiles

41 Conference contribution
40 Article

A fast method to infer Nuclear Magnetic Resonance based effective porosity in carbonate rocks using machine learning techniques
Tariq, Z., Gudala, M., Yan, B., Sun, S. & Mahmoud, M., Jan 11 2023, In: Geoenergy Science and Engineering. p. 211333
Research output: Contribution to journal › Article › peer-review
2 Scopus citations
An Intelligent Safe Well Bottom-Hole Pressure Monitoring of CO2 Injection Well into Deep Saline: A coupled Hydro-Mechanical Approach
Tariq, Z., Yan, B. & Sun, S., Mar 7 2023, Day 1 Sun, February 19, 2023. SPE
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Application of Image Processing Techniques in Deep-Learning Workflow to Predict CO2 Storage in Highly Heterogeneous Naturally Fractured Reservoirs: A Discrete Fracture Network Approach
Tariq, Z., Yan, B. & Sun, S., Mar 7 2023, Day 1 Sun, February 19, 2023. SPE
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
1 Scopus citations
A Robust General Physics-Informed Machine Learning Framework for Energy Recovery Optimization in Geothermal Reservoirs
Xu, Z., Gudala, M., Yan, B., Tariq, Z. & Abdullah, K., 2023, Society of Petroleum Engineers - SPE EuropEC - Europe Energy Conference featured at the 84th EAGE Annual Conference and Exhibition, EURO 2023. Society of Petroleum Engineers, (Society of Petroleum Engineers - SPE EuropEC - Europe Energy Conference featured at the 84th EAGE Annual Conference and Exhibition, EURO 2023).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
Compositional reservoir simulation of underground hydrogen storage in depleted gas reservoirs
Huang, T., Moridis, G. J., Blasingame, T. A., Abdulkader, A. M. & Yan, B., 2023, (Accepted/In press) In: International Journal of Hydrogen Energy.
Research output: Contribution to journal › Article › peer-review
Data driven approach using capacitance resistance model to determine polymer in-situ retention level
Aslam, B., Yan, B., Hidayat, M., Husenido, S., Swadesi, B., Permadi, P. & Marhaendrajana, T., Jul 5 2023, In: Geoenergy Science and Engineering. 229, p. 212043
Research output: Contribution to journal › Article › peer-review
Data-Driven Machine Learning Modeling of Mineral/CO₂/Brine Wettability Prediction: Implications for CO₂ Geo-Storage
Tariq, Z., Ali, M., Yan, B., Sun, S., Khan, M., Yekeen, N. & Hoteit, H., 2023, Society of Petroleum Engineers - Middle East Oil, Gas and Geosciences Show, MEOS 2023. Society of Petroleum Engineers (SPE), (SPE Middle East Oil and Gas Show and Conference, MEOS, Proceedings).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
Deep-Learning-Based Surrogate Model to Predict CO2 Saturation Front in Highly Heterogeneous Naturally Fractured Reservoirs: A Discrete Fracture Network Approach
Tariq, Z., Xu, Z., Gudala, M., Yan, B. & Sun, S., Jan 24 2023, Day 2 Wed, January 25, 2023. SPE
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
1 Scopus citations

Reports Summarize Machine Learning Study Results from King Abdullah University of Science and Technology (KAUST) (A Fast Method To Infer Nuclear Magnetic Resonance Based Effective Porosity In Carbonate Rocks Using Machine Learning Techniques)
Shuyu Sun, Bicheng Yan, Manojkumar Gudala & Zeeshan Tariq
08/22/23
1 item of Media coverage
Press/Media: Press / Media
Findings from King Abdullah University of Science and Technology (KAUST) Broaden Understanding of Energy (Comparison of Supercritical Co2 With Water As Geofluid In Geothermal Reservoirs With Numerical Investigation Using Fully Coupled ...)
Shuyu Sun, Bicheng Yan & Manojkumar Gudala
06/30/23
1 item of Media coverage
Press/Media: Press / Media
Researchers from King Abdullah University of Science and Technology (KAUST) Report Details of New Studies and Findings in the Area of Energy Conversion and Management (Robust Optimization of Geothermal Recovery Based On a Generalized Thermal ...)
Shuyu Sun, Bicheng Yan & Manojkumar Gudala
06/20/23
1 item of Media coverage
Press/Media: Press / Media
Reports from King Abdullah University of Science and Technology (KAUST) Highlight Recent Findings in Fuel Research (Spatial-temporal Prediction of Minerals Dissolution and Precipitation Using Deep Learning Techniques: an Implication To ...)
Shuyu Sun, Hussein Hoteit, Bicheng Yan, Manojkumar Gudala & Zeeshan Tariq
06/2/23
1 item of Media coverage
Press/Media: Press / Media
New Machine Learning Study Findings Has Been Reported by a Researcher at King Abdullah University of Science and Technology (KAUST) (Uncertainty Analysis of CO2 Storage in Deep Saline Aquifers Using Machine Learning and Bayesian Optimization)
Hussein Hoteit & Bicheng Yan
03/1/23
1 item of Media coverage
Press/Media: Press / Media
SPE Reservoir Simulation Conference Conference Scheduled for 28 - 30 Mar 2023
Bicheng Yan
01/20/23
1 item of Media coverage
Press/Media: Press / Media
Research on Mathematics Published by Researchers at King Abdullah University of Science and Technology (KAUST) (Improving deep learning performance for predicting large-scale geological $$(CO}_{2)$$ CO 2 sequestration modeling through feature ...)
Bicheng Yan
12/20/22
1 item of Media coverage
Press/Media: Press / Media
King Abdullah University of Science and Technology (KAUST) Reports Findings in Science (Improving deep learning performance for predicting large-scale geological [Formula: see text] sequestration modeling through feature coarsening)
Bicheng Yan
12/12/22
1 item of Media coverage
Press/Media: Press / Media

Bicheng Yan

Personal profile

Research Interests

Education

Fingerprint

Collaborations and top research areas from the last five years

Dive into details

A fast method to infer Nuclear Magnetic Resonance based effective porosity in carbonate rocks using machine learning techniques

An Intelligent Safe Well Bottom-Hole Pressure Monitoring of CO2 Injection Well into Deep Saline: A coupled Hydro-Mechanical Approach

Application of Image Processing Techniques in Deep-Learning Workflow to Predict CO2 Storage in Highly Heterogeneous Naturally Fractured Reservoirs: A Discrete Fracture Network Approach

A Robust General Physics-Informed Machine Learning Framework for Energy Recovery Optimization in Geothermal Reservoirs

Compositional reservoir simulation of underground hydrogen storage in depleted gas reservoirs

Data driven approach using capacitance resistance model to determine polymer in-situ retention level

Data-Driven Machine Learning Modeling of Mineral/CO₂/Brine Wettability Prediction: Implications for CO₂ Geo-Storage

Deep-Learning-Based Surrogate Model to Predict CO2 Saturation Front in Highly Heterogeneous Naturally Fractured Reservoirs: A Discrete Fracture Network Approach

Reports Summarize Machine Learning Study Results from King Abdullah University of Science and Technology (KAUST) (A Fast Method To Infer Nuclear Magnetic Resonance Based Effective Porosity In Carbonate Rocks Using Machine Learning Techniques)

Findings from King Abdullah University of Science and Technology (KAUST) Broaden Understanding of Energy (Comparison of Supercritical Co2 With Water As Geofluid In Geothermal Reservoirs With Numerical Investigation Using Fully Coupled ...)

Researchers from King Abdullah University of Science and Technology (KAUST) Report Details of New Studies and Findings in the Area of Energy Conversion and Management (Robust Optimization of Geothermal Recovery Based On a Generalized Thermal ...)

Reports from King Abdullah University of Science and Technology (KAUST) Highlight Recent Findings in Fuel Research (Spatial-temporal Prediction of Minerals Dissolution and Precipitation Using Deep Learning Techniques: an Implication To ...)

New Machine Learning Study Findings Has Been Reported by a Researcher at King Abdullah University of Science and Technology (KAUST) (Uncertainty Analysis of CO2 Storage in Deep Saline Aquifers Using Machine Learning and Bayesian Optimization)

SPE Reservoir Simulation Conference Conference Scheduled for 28 - 30 Mar 2023

Research on Mathematics Published by Researchers at King Abdullah University of Science and Technology (KAUST) (Improving deep learning performance for predicting large-scale geological $$(CO}_{2)$$ CO 2 sequestration modeling through feature ...)

King Abdullah University of Science and Technology (KAUST) Reports Findings in Science (Improving deep learning performance for predicting large-scale geological [Formula: see text] sequestration modeling through feature coarsening)

Bicheng Yan

Personal profile

Research Interests

Education

Fingerprint

Collaborations and top research areas from the last five years

Research output

Press/Media