Jianming Zhang | Seismic tomography and inversions | Best Researcher Award

Published on by Petroleum Engineering

Dr. Jianming Zhang | Seismic tomography and inversions | Best Researcher Award

Postdoctoral Researcher at Ocean University of China, China

Zhang Jianming is a rising geophysics researcher recognized for his impactful contributions to seismic tomography and wavefield inversion. As a doctoral candidate at Tongji University, he has led advancements in Eikonal-equation-based methods for seismic velocity modeling, making substantial technical contributions to geophysical imaging and inversion theory. His innovative work has been featured in top-tier journals and international conferences, reflecting his growing influence in both academic and applied geophysics communities. Zhang’s interdisciplinary expertise integrates geophysical modeling, algorithm development, and field-data interpretation, positioning him as a promising early-career scientist.

Profile

Google Scholar

Education

Zhang’s academic foundation is deeply rooted in applied geophysics. He earned his Bachelor’s degree in Applied Geophysics from the China University of Geosciences (Wuhan) in 2019, where he graduated with distinction and was honored for his thesis on 3D source-independent waveform inversion using envelope methods. In the same year, he commenced a direct-entry PhD program in Geophysics at Tongji University. His doctoral research focuses on seismic traveltime tomography based on the Eikonal equation, encompassing adjoint-state methods and anisotropic velocity modeling, which has significantly shaped his research identity.

Experience

Throughout his academic tenure, Zhang has undertaken research at the frontier of seismic imaging. He has developed robust algorithms for fast traveltime computation in vertical transversely isotropic (VTI) media, and has implemented wave-equation-based inversion frameworks for subsurface modeling. Zhang’s experience spans both theoretical development and application to real datasets, with successful field deployments demonstrating the reliability of his methods. He has presented at multiple high-impact conferences such as EAGE, SEG, and IMAGE, often contributing as a lead author and speaker. His active role as a reviewer for journals such as Geophysics and Geophysical Prospecting attests to his engagement and credibility in the professional community.

Research Interest

Zhang’s research interests include geophysical modeling and inversion, particularly seismic traveltime and waveform inversion, Eikonal solvers, and elastic wave propagation in anisotropic media. He is passionate about integrating numerical methods with field data to resolve complex geological structures. His work focuses on increasing computational efficiency and accuracy in seismic tomography, especially through innovations in first-arrival and reflection waveform techniques. He is also engaged in wave-equation modeling and multi-parameter inversion strategies tailored for VTI media, with applications in both academia and the energy industry.

Awards

Zhang received the Wiley “Top Downloaded Article” Award in 2023 for his co-authored work on preconditioned transmission and reflection joint traveltime tomography, published in Geophysical Prospecting. This award highlights the relevance and reach of his contributions in the geophysical community. In addition to journal recognition, his work has been featured in key oral and poster sessions at international geoscience conferences, often spotlighted for methodological novelty and practical impact.

Publications

Among Zhang’s many publications, the following represent the breadth and depth of his research contributions:

  1. Zhang J., Dong L., Liu Y., et al. (2025). “Eikonal-equation-based elastic velocities reconstruction for multi-component seismic reflection data.” Geophysics, 90(4), U47–U58. [Cited by 4 articles]

  2. Zhang J., Dong L., Huang C. (2024). “A shortest-path-aided fast sweeping method in VTI media.” Geophysical Prospecting, 72(7), 2761–2771. [Cited by 6 articles]

  3. Zhang J., Dong L., Wang J., et al. (2024). “Adjoint-state characteristic reflection traveltime tomography.” Geophysics, 89(1), U17–U30. [Cited by 5 articles]

  4. Zhang J., Dong L., Wang J., et al. (2023). “Preconditioned transmission + reflection joint tomography.” Geophysical Prospecting, 71(2), 171–190. [Cited by 12 articles]

  5. Zhang J., Dong L., Wang J., Wang Y. (2023). “Illumination compensation in VTI media.” Journal of Applied Geophysics, 211, 104964. [Cited by 3 articles]

  6. Zhang J., Dong L., Wang J., Wang Y. (2022). “Multi-parameter traveltime inversion in VTI media.” Chinese Journal of Geophysics, 65(10), 4028–4046. [Cited by 8 articles]

  7. Dong L., Zhang J., Han P. (2021). “Improved traveltime tomography via adjoint-state method.” Chinese Journal of Geophysics, 64(3), 982–992. [Cited by 7 articles]

Conclusion

Zhang Jianming exemplifies the qualities of a promising geophysicist through his methodological innovations, peer-reviewed publications, and international recognition. His focused research on Eikonal-equation-based traveltime tomography and anisotropic inversion models advances both the theoretical and practical aspects of geophysics. His work is highly cited, and his contributions have already impacted seismic imaging practices in both academia and industry. With a strong trajectory of achievement, Zhang is an exceptional candidate for recognition through this award nomination.

Xiaojun Tang | Well logging | Best Researcher Award

Published on by Petroleum Engineering

Prof. Xiaojun Tang | Well logging | Best Researcher Award

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:

  1. “FTIR-based detection of water vapor in wellhead gas for aquifer identification,” Journal of Petroleum Science and Engineering, 2021, cited by 32 articles.

  2. “Spectral analysis in well logging: Application of intelligent algorithms,” Sensors and Actuators B: Chemical, 2020, cited by 45 articles.

  3. “A new intelligent gas logging sensor system for low-permeability reservoirs,” IEEE Sensors Journal, 2019, cited by 28 articles.

  4. “Infrared spectral inversion model for mud gas analysis,” Fuel, 2022, cited by 18 articles.

  5. “Smart instrumentation in downhole monitoring: A review,” Measurement, 2018, cited by 50 articles.

  6. “Hybrid sensor fusion for coalbed methane detection,” Energy Exploration & Exploitation, 2023, cited by 10 articles.

  7. “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.