Dandan Zhu | Intelligent Drilling and Completion | AI and Automation in Petroleum Award

Published on by Petroleum Engineering

Assoc. Prof. Dr. Dandan Zhu | Intelligent Drilling and Completion | AI and Automation in Petroleum Award

Associate Professor at China University of Petroleum, Beijing, China

Dr. Dandan Zhu is an accomplished Associate Professor at the China University of Petroleum, Beijing, in the College of Artificial Intelligence. With a strong academic foundation and innovative research output, she has emerged as a prominent expert in the integration of artificial intelligence with petroleum engineering. Her pioneering work in intelligent drilling technologies and wellbore guidance systems has advanced subsurface automation and decision-making under uncertainty. Dr. Zhu has led numerous national projects and maintains deep collaborative ties with China’s top energy enterprises. Through publications, patents, and cross-disciplinary innovations, she has significantly contributed to the modernization of petroleum exploration and production.

Profile

Google Scholar

Education

Dr. Zhu holds a Ph.D. in Precision Engineering from the University of Tokyo, where she developed advanced modeling tools for mechanical systems. Prior to this, she earned a Master’s degree in Aircraft Design from Beihang University, building her expertise in computational mechanics and control. This unique academic trajectory provided her with a solid grounding in both high-precision design and intelligent control systems, which later became central to her work in petroleum AI. Her educational foundation is characterized by a rigorous blend of systems engineering, applied mathematics, and programming, equipping her to bridge the gap between AI theory and practical energy applications.

Experience

Since joining the China University of Petroleum in 2015, Dr. Zhu has led over 40 national and provincial-level research projects, many in collaboration with energy industry leaders such as CNPC, Sinopec, and CNOOC. She has executed 27 consultancy and industry-sponsored projects, developing intelligent geo-steering, simulation environments, and adaptive drilling systems. Her responsibilities extend beyond research to include mentoring graduate students and integrating AI pedagogy into petroleum engineering curricula. Her professional trajectory reflects a deep commitment to both academic excellence and industrial application. Her field-tested tools and platforms demonstrate practical outcomes in hydraulic fracturing, reservoir modeling, and real-time trajectory control.

Research Interest

Dr. Zhu’s research focuses on the intersection of artificial intelligence and petroleum engineering, specifically intelligent drilling systems, reinforcement learning for wellbore trajectory control, and real-time decision-making in geo-steering. She has built generative simulation environments that replicate subsurface dynamics for training AI agents. A key innovation includes a high-interaction learning framework that integrates offline modeling, real-time drilling guidance, and strategic post-drilling analysis. Her recent work emphasizes robustness and adaptability in drilling operations by accounting for geological uncertainty. Through deep reinforcement learning, data-driven optimization, and control theory, Dr. Zhu is contributing to the intelligent automation of energy exploration systems.

Award

Dr. Zhu’s impactful research has positioned her as a strong candidate for the Best Researcher Award in Petroleum Engineering. Her innovations have earned recognition across academia and industry. She has received multiple provincial and institutional grants to pursue advanced simulation and AI research. Her patented technologies in wellbore trajectory control and geo-steering optimization are used in field applications. Furthermore, her interdisciplinary efforts have been integral to national science and technology programs in China. These accolades, combined with her extensive collaboration with major energy corporations, underscore her standing as a leading researcher advancing AI integration in energy systems.

Publication

Dr. Zhu has published 39 peer-reviewed journal articles, contributing significantly to petroleum AI literature. Select publications include:

  1. A target-aware well path control method based on transfer reinforcement learning.

  2. Gait coordination feature modeling and multi-scale gait representation for gait recognition.

  3. PPS-QMIX: Periodically Parameter Sharing for Accelerating Convergence of Multi-Agent Reinforcement Learning

  4. An intelligent drilling guide algorithm design framework based on high interactive learning mechanism

  5. End-to-end multiplayer violence detection based on deep 3D CNN

  6. Investigation on automatic recognition of stratigraphic lithology based on well logging data using ensemble learning algorithm

  7. A reinforcement learning based 3d guided drilling method: Beyond ground control

Her work has received over 68 citations since 2020 and continues to shape the AI-petroleum research landscape.

Conclusion

Dr. Dandan Zhu exemplifies the integration of technical innovation and practical relevance in petroleum engineering. Through her work in artificial intelligence, simulation, and intelligent control, she is reshaping the way subsurface operations are conceptualized and executed. Her contributions extend beyond academic theory into field-proven tools and methods widely adopted by industry leaders. By mentoring future engineers, publishing transformative research, and collaborating across sectors, she has established herself as a thought leader at the intersection of AI and energy. Her continued contributions reflect not only technical excellence but also a visionary approach to sustainable and intelligent resource development.

Bei Gao | Petroleum Engineering | Best Researcher Award

Published on by Petroleum Engineering

Mrs. Bei Gao | Petroleum Engineering | Best Researcher Award

Reservoir Domain Champion at Schlumberger, China

Gao Bei, MSc., BSc., is an accomplished reservoir engineer with extensive experience in managing complex technical and investigative projects in the oil and gas industry. With a strong foundation in reservoir simulation, well testing, and formation evaluation, Gao has built a reputation for delivering superior results to both clients and internal stakeholders. Her expertise extends to project management, stakeholder engagement, and technical consultation, particularly in high-pressure, high-temperature reservoirs. She has successfully worked with major oil companies, including CNOOC, Husky, JAPEX, and INPEX, and has played a significant role in advancing reservoir characterization methodologies. Gao has also contributed significantly to the petroleum industry by publishing research papers, acquiring patents, and leading technical initiatives in various international forums.

Profile

Scopus

Education

Gao Bei holds a Master of Science (MSc) in Chemical Engineering from Manchester University, UK, obtained in 2003. She completed her Bachelor of Science (BSc) in Chemical Engineering at East China University in Shanghai, China, in 2000. Her academic background provided a strong foundation in chemical and petroleum engineering principles, which she has applied throughout her career in reservoir engineering and formation analysis.

Experience

Gao Bei has an extensive career in the petroleum industry, with key roles in international organizations. Since 2017, she has been serving as the Reservoir Domain Champion at Schlumberger, overseeing formation testing technologies and advising on reservoir challenges in China, Japan, and Taiwan. Previously, she worked as a Senior Reservoir Engineer in the UK, managing reservoir simulation workflows and leading major client projects. From 2009 to 2011, she led a team of engineers in Beijing, China, focusing on formation analysis and developing new workflows. Earlier roles include working as a Reservoir Engineer in Russia and Angola, where she conducted well testing, formation pressure monitoring, and fluid analysis. Her ability to manage cross-functional teams and drive technical innovations has been instrumental in her career progression.

Research Interests

Gao Bei’s research interests lie in reservoir fluid geodynamics, downhole fluid analysis, high-pressure high-temperature reservoir evaluations, and gas hydrate disassociation. She has explored innovative methodologies for integrating numerical simulation techniques with real-time field data to optimize reservoir performance. Her work in reservoir connectivity and production prediction has influenced industry practices, particularly in the application of advanced fluid characterization techniques. Additionally, she is interested in the commercialization of reservoir simulation technologies and the development of new workflows for improved well performance evaluation.

Awards

Gao Bei has been recognized for her contributions to the petroleum industry with multiple copyrights and patents. Notably, she was awarded a patent for “Method and System for Fluid Characterization of a Reservoir,” which has been widely adopted in reservoir studies. Her innovative work has also earned her accolades within Schlumberger and from industry associations, acknowledging her technical leadership and contributions to reservoir engineering advancements.

Publications

Gao Bei has authored and co-authored several technical papers presented at international petroleum conferences. Some of her notable publications include:

“Comprehensive Production Evaluation for Gas Condensate at Early Exploration Stage by Using Downhole Fluid Analysis DFA and Numerical Simulation: Case Study from China Bohai Bay” – SPE Russian Petroleum Technology Conference, 2018.

“Productivity Evaluation of Pronounced Heterogeneous Gas Reservoir Drilled at High Overbalance” – 24th Formation Evaluation Symposium of Japan, 2018.

“New Method for Disassociate Rate and Permeability Evaluation in Gas Hydrate” – AAPG GTW, Auckland, New Zealand, 2019.

“Reservoir Fluid Geodynamics, a New Way to Evaluate the Reservoir Connectivity” – IPTC 2019.

“Using Asphaltene Nano-Science to Guide Geology Realization and Field Development” – IPTC 2019.

“Case Study: Uncertainty Analysis of Reservoir Parameters in Low Resistivity Heavy Oil Reservoir to Understand Reservoir Performance” – 24th Formation Evaluation Symposium of Japan, 2018.

“Integrated Case Study from Reservoir Characterization to Improved Well Performance Evaluation in Abnormal HPHT Tight Gas Reservoir” – AAPG Annual Conference, San Antonio, TX, USA, 2019.

Conclusion

Gao Bei’s career exemplifies dedication, technical expertise, and leadership in reservoir engineering. With a strong academic background, extensive industry experience, and a passion for research and development, she has made significant contributions to the oil and gas sector. Her ability to integrate advanced technologies into reservoir evaluations, combined with her commitment to knowledge-sharing and stakeholder engagement, has positioned her as a leading figure in the field. Through her publications, patents, and mentorship roles, she continues to drive innovations and shape the future of reservoir engineering.