
Yuanjun Li
Ph.D. Student in Energy Resources Engineering
Bio
Yuanjun Li is a PhD Candidate from Energy Resources Engineering. She is currently working on application of deep learning approaches for well data history regeneration at SUPRI-D research group. She is also a member from Smart Field Consortium (SFC).
Honors & Awards
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LASPE Scholarship - Graduate Student Awards of Excellence, SPE-LA (2018)
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University Scholarship - Excellent Student Awards, CUPB (2015)
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National Scholarship, CSC (2014)
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Enterprise Scholarship - Excellent Student Awards, SINOPEC (2013)
Education & Certifications
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PhD, Stanford University, Energy Resources Engineering (2022)
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MS, University of Southern California, Petroleum Engineering (2018)
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BS, China University of Petroleum, Beijing, Oil-Gas Storage&Transportation Engineering (2016)
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Exchange Scholar, University of Tulsa, Petroleum Engineering (2014)
Current Research and Scholarly Interests
- Application of deep learning approaches for pressure history regeneration.
- Smart oilfield technologies and oilfield optimization
- Time series production data analysis with deep learning
All Publications
- Prediction of Penetration Rate Ahead of the Bit Through Real-Time Updated Machine Learning Models Society of Petroleum Engineers. 2019
- Deep Learning for Well Data History Analysis Society of Petroleum Engineers. 2019
- Dynamic Layered Pressure Map Generation in a Mature Waterflooding Reservoir Using Artificial Intelligence Approach Society of Petroleum Engineers. 2018
- Reservoir Ranking Map Sketching for Selection of Infill and Replacement Drilling Locations Using Machine Learning Technique Society of Petroleum Engineers. 2018
- Reservoir Geostatistical Estimation of Imprecise Information Using Fuzzy Kriging Approach Society of Petroleum Engineers. 2018