Professor at Xi’an Jiaotong University, China
Professor Xiaojun Tang is a leading academic in the field of intelligent detection systems applied to petroleum engineering. He currently serves at Xi’an Jiaotong University within the School of Instrumentation Science and Technology, where he also directs the Institute of Intelligent Detection Technology and Systems. With an emphasis on innovation and interdisciplinary integration, his academic journey has yielded substantial contributions in well/gas logging, spectral analysis, and intelligent instrumentation systems. He is a seasoned researcher with over 60 publications, 50 patents, and numerous prestigious awards recognizing his technological contributions to petroleum engineering and instrumentation.
Profile
Scopus
Education
Professor Tang’s academic foundation was laid through rigorous scientific training, culminating in a Ph.D. with specialization in instrumentation and signal analysis applied to petroleum applications. His doctoral research sparked his career-long focus on intelligent sensor systems, spectral diagnostics, and well-logging instrumentation. This advanced academic background has informed his leadership in developing frontier technologies that intersect physics, data science, and geoscience for enhanced subsurface exploration.
Experience
Over the years, Professor Tang has accumulated extensive experience in both academia and applied research. At Xi’an Jiaotong University, he has been instrumental in building an ecosystem of innovation that integrates academic research with practical industrial applications. His role as the director of the Institute of Intelligent Detection Technology and Systems highlights his leadership in organizing large-scale collaborative projects. He has spearheaded over 50 major scientific research projects, including those under China’s National Key Scientific Instrument Program and the National Natural Science Foundation. Beyond academia, he has engaged with industry partners such as PetroChina, CNOOC, and Changqing Oilfield, translating research outcomes into actionable field solutions.
Research Interest
Professor Tang’s research interests revolve around intelligent detection technologies for petroleum engineering, particularly in well logging, gas analysis, and mud logging. A key area of his focus is the development and deployment of spectral analysis technologies, notably FTIR (Fourier-transform infrared spectroscopy), for wellhead gas diagnostics. His pioneering work in applying FTIR technology has led to novel techniques for identifying aquifers based on water vapor signatures. These contributions have significantly improved reservoir characterization in low-resistivity and low-porosity formations, addressing long-standing challenges in hydrocarbon exploration. His interests also extend to coal mine gas safety and intelligent sensor systems, underscoring a broader commitment to energy sector innovation and safety.
Award
Professor Tang’s exceptional contributions have been recognized through multiple prestigious awards. He is a recipient of the Shaanxi Science and Technology Achievement Award (Second Prize), the Liaoning Science and Technology Progress Award (First Prize), and the Innovation Award from the China Instrument Society. These accolades reflect both the originality and practical utility of his research, particularly in the development of advanced instrumentation and data-driven diagnostics for petroleum exploration. His standing as a distinguished researcher is further validated by his h-index of 16 on Scopus, underscoring the significant impact and citation of his work in the scientific community.
Publication
Professor Tang’s scholarly work has been widely disseminated in high-impact journals. His notable publications include:
-
“FTIR-based detection of water vapor in wellhead gas for aquifer identification,” Journal of Petroleum Science and Engineering, 2021, cited by 32 articles.
-
“Spectral analysis in well logging: Application of intelligent algorithms,” Sensors and Actuators B: Chemical, 2020, cited by 45 articles.
-
“A new intelligent gas logging sensor system for low-permeability reservoirs,” IEEE Sensors Journal, 2019, cited by 28 articles.
-
“Infrared spectral inversion model for mud gas analysis,” Fuel, 2022, cited by 18 articles.
-
“Smart instrumentation in downhole monitoring: A review,” Measurement, 2018, cited by 50 articles.
-
“Hybrid sensor fusion for coalbed methane detection,” Energy Exploration & Exploitation, 2023, cited by 10 articles.
- “Mathematical modeling of water vapor features in reservoir diagnostics,” Journal of Natural Gas Science and Engineering, 2021, cited by 21 articles.
These publications collectively illustrate Professor Tang’s commitment to solving complex problems through technological innovation and interdisciplinary research.
Conclusion
Professor Xiaojun Tang exemplifies excellence in petroleum engineering through his sustained contributions to intelligent detection technology. His work bridges academic insight and field application, advancing both theory and practice in subsurface diagnostics. With a strong record of leadership in high-profile research projects, extensive publications, and impactful industry collaborations, he stands out as a pioneer in applying spectral and intelligent instrumentation techniques to petroleum exploration. His achievements have not only influenced the academic community but also directly enhanced operational efficiency and safety in the field. In recognition of his contributions, Professor Tang is a highly deserving candidate for the Best Researcher Award in petroleum engineering.