Said Gaci | Geophysics Reservoir Characterization | Best Researcher Award

Published on by Petroleum Engineering

Dr. Said Gaci | Geophysics Reservoir Characterization | Best Researcher Award

Head of Technical and Scientific Support for R&D at Sonatrach-DC R&D, Algeria

Dr. Said Gaci is an accomplished geophysicist and research leader with extensive expertise in hydrocarbon exploration, signal processing, and petroleum reservoir analysis. Currently serving as the Director of Scientific and Technical Support for R&D at Sonatrach, he has built a distinguished career in Algeria’s energy sector, integrating scientific innovation with operational excellence. Dr. Gaci is renowned for introducing advanced seismic methods and machine learning techniques into geophysical workflows, significantly improving subsurface characterization. His professional footprint includes over two decades of experience, major collaborations with academic and industry partners, and a prolific record of publishing influential books and journal articles in petroleum geoscience.

Profile

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Education

Dr. Gaci holds multiple advanced degrees, reflecting a strong interdisciplinary academic foundation. He received his Engineer diploma in Geophysics in 1997 and a Magister degree in Petroleum Economics and Strategic Management in 2004 from the Algerian Petroleum Institute. Simultaneously, he earned another Magister degree in Geophysics in 2002, followed by a Ph.D. in 2011 from the University of Sciences and Technology Houari Boumediene (USTHB), Algeria. His doctoral work focused on multifractional analysis of geophysical signals, which became foundational to many of his later innovations in reservoir modeling. He also holds a habilitation to supervise research, granted in 2016.

Experience

Dr. Gaci has accumulated over 20 years of professional experience in geophysics and energy research. From 2004 to 2015, he served in multiple technical roles at Sonatrach’s Exploration Division. He later led R&D departments and training divisions at the Algerian Petroleum Institute from 2015 to 2024. Since October 2024, he has headed the scientific and technical support for Sonatrach’s Central R&D Directorate. His portfolio includes supervising multidisciplinary teams on seismic interpretation, economic feasibility, and reservoir analysis. In parallel, he contributed as a part-time lecturer and regularly collaborates with international institutions on energy-related projects and theses.

Research Interest

Dr. Gaci’s research focuses on advanced geophysical signal processing, reservoir characterization, empirical mode decomposition, and machine learning in seismic data analysis. He has introduced multifractional Brownian motion models for interpreting heterogeneities in borehole data and pioneered methods integrating AI with traditional seismic attributes. His work aims to improve fluid detection and lithological segmentation in complex subsurface environments. He continues to explore applications in geothermal energy and carbon storage, using AI and fractal geometry. He has completed multiple international consulting and industry research projects, applying cutting-edge techniques to real-world petroleum challenges.

Awards

Dr. Gaci has gained recognition for his scientific leadership and technical excellence. He serves on editorial boards of reputed journals such as Arabian Journal of Geosciences and Frontiers in Earth Science. He has chaired and co-convened numerous international conferences, including sessions at the EGU General Assembly and AAPG events. Additionally, he was appointed as a university qualification expert by Algeria’s Ministry of Higher Education. His achievements include several awards for research excellence and invited roles in global geoscience forums.

Publications

Dr. Gaci has published over 40 journal articles and authored seven technical books. Selected recent publications include:

  1. Machine Learning and Seismic Attributes for Petroleum Prospect Generation and Evaluation (2025, Interpretation Journal)

  2. Petrophysical evaluation using CNNs in Berkine Basin (2024, Journal of Engineering Research)

  3. Advanced signal and pattern recognition in geosciences (2023, Frontiers in Earth Science)

  4. A Grey System Approach for Hölderian Regularity Estimation (2021, Fractal and Fractional).

  5. Investigation of lithological heterogeneities using EMD-Hölder (2022, Journal of Petroleum Science and Engineering)

  6. Seismic attributes for hydrocarbon detection in Australia (2021, Arabian Journal of Geosciences).

  7. Spectral and amplitude decomposition for fluid detection (2020, Journal of Seismic Exploration).

These publications demonstrate his high-impact contributions to petroleum geophysics and applied research.

Conclusion

In conclusion, Dr. Said Gaci stands as a leading figure in petroleum geophysics, blending academic rigor with real-world application. His interdisciplinary expertise, from signal theory to economic modeling, has transformed how seismic data are interpreted and utilized for hydrocarbon exploration. With numerous publications, pioneering research, and international collaborations, he continues to push the boundaries of what is technically possible in reservoir characterization.

Ida Lykke Fabricius | Petrophysics and Rock Physics | Best Researcher Award

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Prof. Dr. Ida Lykke Fabricius | Petrophysics and Rock Physics | Best Researcher Award

Professor Emerita at Technical University of Denmark, Denmark

Ida Lykke Fabricius is a distinguished geoscientist whose career spans over four decades of impactful contributions to sedimentary rock physics and geotechnical engineering. Currently Professor Emerita at DTU Sustain, she has played a central role in bridging the gap between academic research and applied geoscience, particularly within the domains of sediment mechanics, rock physics, and reservoir characterization. Her legacy is reflected not only in her extensive publication record but also in her leadership within Danish and Scandinavian scientific institutions. Fabricius has continuously advanced the understanding of how sedimentary rock properties evolve under geological processes, guiding the development of energy, environmental, and civil infrastructure projects.

Profile

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Education

Fabricius’s academic journey began with an MSc in Geology from the University of Copenhagen in 1981, where she was awarded the prestigious Gold Medal. She went on to earn her PhD in 1988 at the Institute of Applied Geology at the Technical University of Denmark (DTU), focusing on the physical behavior of geological materials. Her academic pursuit culminated in a Dr. techn. degree in 2009 from DTU’s Department of Environmental Engineering, affirming her status as a leading authority in her field. Her progressive academic training reflects a continuous and deepening specialization in geotechnical and geological engineering.

Experience

With a career marked by steady advancement and scientific leadership, Fabricius began as a Development Geologist at Mærsk Oil and Gas (1981–1985) before transitioning to academia. From 1985 to 1988, she served as an Assistant Professor/PhD student at DTU, moving into an Associate Professor role until 2011. She took on early leadership as Head of Department in Geology and Geotechnical Engineering from 1989 to 1992, and later held the positions of Professor MSO (2011–2016), Head of Section (2012–2022), and Professor (2016–2024) at the Department of Civil Engineering, DTU. Internationally, she also contributed as Professor II at the University of Stavanger (2014–2018). Her transition to Professor Emerita in 2024 marks a continuing commitment to mentoring and scientific dialogue.

Research Interest

Fabricius’s research centers on the physical properties of sediments and sedimentary rocks, particularly in relation to pore fluid composition, pressure, temperature, and diagenesis. Her work integrates laboratory measurements with field data, enabling robust models for mechanical behavior and acoustic properties of sedimentary formations. She has contributed significantly to linking rock physics and rock mechanics, with applications ranging from hydrocarbon exploration to sustainable subsurface infrastructure. Her interdisciplinary approach has helped to unify geotechnical engineering, geophysics, and petrophysics into actionable scientific frameworks.

Award

Throughout her career, Fabricius has received notable honors that underscore her technical leadership and service. In 2023, she received the SPE Copenhagen Award for Outstanding Technical & Academic Contributions, a recognition of her influence in petroleum geoscience. She was knighted as “Ridder af Dannebrogsordenen” in 2019, reflecting national recognition of her contributions to science. Earlier distinctions include the Direktør Gorm-Petersens Mindelegat in 1989 and the University of Copenhagen Gold Medal in 1981. These awards affirm both her early promise and long-standing excellence.

Publication

Fabricius has authored over 98 Web of Science-indexed articles with 2,730 citations and an h-index of 30, reflecting her sustained influence in geoscience. Some notable publications include:

  1. Fabricius, I. L. (2003). “How burial diagenesis affects chalk porosity.” AAPG Bulletin, cited by 289 articles.

  2. Fabricius, I. L., et al. (2007). “Petrophysical properties of chalk: pore structure and acoustic velocity.” Petroleum Geoscience, cited by 174 articles.

  3. Fabricius, I. L., & Baechle, G. (2009). “Elastic moduli of chalk and pore system properties.” Geophysics, cited by 141 articles.

  4. Fabricius, I. L., et al. (2008). “Effect of temperature and salinity on acoustic velocity in chalk.” Geophysical Prospecting, cited by 97 articles.

  5. Fabricius, I. L. (2006). “Pore pressure prediction from acoustic data.” Marine and Petroleum Geology, cited by 85 articles.

  6. Fabricius, I. L., & Røgen, B. (2001). “Strength and porosity of chalk from the North Sea.” Journal of Petroleum Science and Engineering, cited by 76 articles.

  7. Fabricius, I. L., et al. (2010). “Velocity–porosity transforms in chalk.” Geophysical Journal International, cited by 69 articles.

These selected publications highlight her integrative and data-driven approach to understanding chalk and sedimentary systems.

Conclusion

Professor Ida Lykke Fabricius has established herself as a cornerstone of geoscientific advancement in Denmark and beyond. Her pioneering research in sedimentary rock physics has shaped both theoretical understanding and practical applications in petroleum engineering, geotechnics, and environmental geoscience. Her leadership roles, high-impact publications, and national honors reflect a lifetime of dedication to scientific integrity, innovation, and education. Fabricius remains a role model for emerging geoscientists, combining rigorous analysis with a collaborative and visionary approach to earth sciences.

Christopher Mkono | Artificial Intelligence in Petroleum Engineering | Best Researcher Award

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Mr. Christopher Mkono | Artificial Intelligence in Petroleum Engineering | Best Researcher Award

Student at China university of Geosciences (Wuhan), China

Christopher Nyangi Mkono is a PhD candidate in Oil and Natural Gas Engineering at the China University of Geosciences, with a specialized focus on machine learning applications in source rocks potentiality, reservoir characterization, and hydrocarbon resource evaluation. He is deeply involved in the integration of artificial intelligence and machine learning models to enhance the understanding and management of subsurface resources. With a solid academic foundation, Mkono has contributed significantly to the fields of geosciences and petroleum engineering, blending his expertise in programming and numerical modeling with an understanding of geotechnical systems. His work has spanned multiple global platforms, presenting at key international conferences and contributing to cutting-edge research in the energy sector.

Profile

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Education

Mkono’s educational journey is marked by a commitment to advancing his knowledge in oil and gas engineering. He is currently pursuing a PhD at the China University of Geosciences, where he began his master’s program in 2019. Before that, he completed his Bachelor of Science in Applied Geology from the University of Dodoma, Tanzania, in 2016. This academic trajectory highlights a strong foundation in geosciences, complemented by advanced studies in petroleum engineering. His research combines theoretical and practical applications, particularly in the development of innovative computational models and machine learning techniques for resource estimation.

Experience

Christopher Mkono has gained significant experience in the fields of geosciences and petroleum engineering, focusing on innovative approaches to reservoir characterization and hydrocarbon potential analysis. His work involves the application of neural network algorithms, machine learning techniques, and artificial intelligence to improve the accuracy and efficiency of geophysical and geochemical analyses. Additionally, he is proficient in various programming languages, including MATLAB and Python, and has worked extensively with scientific software and numerical modeling tools such as Origin and Eclipse. This expertise enables him to manage databases and develop models that support the energy industry’s evolving needs.

Research Interests

Mkono’s research interests lie primarily in the intersection of machine learning and geosciences, with a particular focus on the application of these technologies in source rock evaluation and hydrocarbon resource prediction. His work aims to improve the understanding of subsurface geology by integrating advanced artificial intelligence techniques with traditional geological modeling. Mkono is particularly interested in improving the estimation of reservoir properties such as porosity and permeability, utilizing models that incorporate explainable artificial intelligence for greater transparency and interpretability in results. His research also extends to reservoir thermal maturity estimation and the application of hybrid machine learning approaches in basin modeling.

Awards

Throughout his academic career, Christopher Mkono has demonstrated exceptional academic and research potential. While still early in his career, his contributions to geosciences and petroleum engineering have been recognized at several levels, particularly his work in integrating AI into traditional geological processes. His innovative contributions have earned him opportunities to present at prominent international conferences and competitions, such as the China Petroleum Engineering Design Competition International Circuit. His ongoing contributions to his field position him as a promising researcher whose work is poised for significant impact in both academic and industrial contexts.

Publications

Christopher Mkono has authored several notable publications in high-impact journals, focusing on the application of machine learning and artificial intelligence in geosciences. His research has been well received by the academic community, with articles published in journals such as SPE Journal and Engineering Applications of Artificial Intelligence. A few of his key publications include:

Mkono, C. N., Chuanbo, S., Mulashani, A. K., Abelly, E. N., Kasala, E. E., Shanghvi, E. R., Emmanuely, B. L., & Mokobodi, T. (2025). “Improved Reservoir Porosity Estimation Using an Enhanced Group Method of Data Handling with Differential Evolution Model and Explainable Artificial Intelligence.” SPE Journal, 1-19.

Mkono, C. N., Shen, C., Mulashani, A. K., Carranza, E. J. M., Kalibwami, D. C., & Nyangi, M. J. (2025). “A Novel Hybrid Group Method of Data Handling and Levenberg Marquardt Model for Estimating Total Organic Carbon in Source Rocks with Explainable Artificial Intelligence.” Engineering Applications of Artificial Intelligence, 144, 110137.

Mkono, C. N., Shen, C., Mulashani, A. K., Mwakipunda, G. C., Nyakilla, E. E., Kasala, E. E., & Mwizarubi, F. (2025). “A Novel Hybrid Machine Learning and Explainable Artificial Intelligence Approaches for Improved Source Rock Prediction and Hydrocarbon Potential in the Mandawa Basin, SE Tanzania.” International Journal of Coal Geology, 104699.

Mkono, C. N., Shen, C., Mulashani, A. K., Ngata, M. R., & Hussain, W. (2024). “A Novel Hybrid Machine Learning Approach and Basin Modeling for Thermal Maturity Estimation of Source Rocks in Mandawa Basin, East Africa.” Natural Resources Research, 33(5), 2089-2112.

Mkono, C. N., Shen, C., Mulashani, A. K., & Nyangi, P. (2024). “An Improved Permeability Estimation Model Using Integrated Approach of Hybrid.”

These works reflect his expertise in enhancing the accuracy of geological assessments using artificial intelligence, with many of his papers garnering significant citations from both academic and industry professionals.

Conclusion

Christopher Mkono is an emerging scholar in the field of petroleum engineering, with a solid background in geosciences and a passion for integrating machine learning and artificial intelligence into his research. His work is positioned to make significant contributions to the fields of source rock analysis, reservoir characterization, and hydrocarbon resource evaluation. Through his publications, presentations, and participation in international conferences, Mkono is building a reputation as a forward-thinking researcher whose work will help shape the future of geosciences and petroleum engineering. His ongoing efforts in advancing AI applications in geosciences reflect both his academic potential and his commitment to addressing the challenges of energy resource management.