Said Gaci | Geophysics Reservoir Characterization | Best Researcher Award

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.

Tahir Cetin Akinci | Data Analytics in Upstream Operations | Best Research Article Award

Dr. Tahir Cetin Akinci | Data Analytics in Upstream Operations | Best Research Article Award

Scientist at University of California Riverside, United States

Dr. Tahir Çetin Akıncı is a distinguished academician and researcher in electrical engineering, particularly known for his impactful work in artificial intelligence, renewable energy, and advanced signal processing. With a professional trajectory that spans over two decades, he has consistently contributed to advancing knowledge and innovation in intelligent systems and power electronics. His commitment to both academic excellence and real-world problem-solving has earned him global recognition, positioning him as a thought leader in his field.

Profile

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Education

Dr. Akıncı began his academic journey at Klaipeda University in Lithuania, earning his undergraduate degree in electrical engineering in 2000. He later pursued graduate studies at Marmara University, where he completed his master’s degree in 2005 and Ph.D. in 2010. These formative academic experiences laid the groundwork for his future research directions, particularly in the domains of energy systems and machine learning applications. His educational path is marked by a solid foundation in electrical systems theory, enriched by practical insights into data-driven methodologies.

Experience

His professional career commenced as a Research Assistant at Marmara University, where he served from 2003 to 2010. He then joined Istanbul Technical University (ITU), advancing through academic ranks to become a full professor by 2020. Currently, Dr. Akıncı serves at the University of California, Riverside, contributing to international collaborations and high-impact research initiatives. Throughout his tenure in academia, he has mentored students, led research projects, and collaborated across disciplines to address critical engineering challenges.

Research Interest

Dr. Akıncı’s research interests are both broad and deep, encompassing renewable energy systems, artificial neural networks, deep learning, machine learning, cognitive systems, signal processing, and data analysis. His multidisciplinary approach allows him to tackle complex problems—ranging from optimizing photovoltaic systems to diagnosing electrical motor faults using AI. His work in renewable energy technologies and smart systems not only enhances system efficiencies but also aligns with global sustainability goals. He is particularly passionate about the integration of AI in diagnostics, predictive maintenance, and energy management, striving to create systems that are not only intelligent but also resilient and sustainable.

Award

His contributions have been recognized through multiple prestigious awards, most notably the International Young Scientist Excellence Award and the Best Researcher Award in 2022. These accolades reflect his pioneering work and the high regard he holds within the scientific community. In addition to these honors, Dr. Akıncı has played critical roles as editor and guest editor for leading journals and serves on scientific committees of several high-profile international conferences, further underscoring his influence in shaping future directions in electrical engineering and AI.

Publication

Among his extensive list of publications, several recent papers stand out for their innovative approaches and significant citations. For instance:

“Sustainable pathways for hydrogen production: Metrics, trends, and strategies for a zero-carbon future,” Sustainable Energy Technologies and Assessments, 2025 – cited for its strategic insights on green hydrogen.

“Revealing GLCM Metric Variations across Plant Disease Dataset,” Electronics, 2024 – contributes to deep learning applications in agriculture.

“Optimization of Neuro-controller Application for MPPT in Photovoltaic Systems,” Electric Power Components and Systems, 2024 – enhances energy efficiency using AI.

“Time Series Forecasting Utilizing AutoML,” Information, 2024 – applies automated ML for forecasting in diverse datasets.

“Advanced Dual RNN Architecture for Electrical Motor Fault Classification,” IEEE Access, 2023 – highly cited for its innovation in motor diagnostics.

“Machine Learning-Based Error Correction Codes and Communication Protocols for Power Line Communication,” IEEE Access, 2023 – strengthens smart grid reliability.

“Effect of LED Light Frequency on an Object in Terms of Visual Comfort,” Electric Power Components and Systems, 2024 – explores visual ergonomics in energy-efficient lighting.

Conclusion

In conclusion, Dr. Tahir Çetin Akıncı exemplifies the ideal candidate for this award through his unwavering commitment to scientific advancement, innovation in engineering education, and leadership in multidisciplinary research. His work bridges the gap between theory and application, aiming to develop technologies that not only solve current engineering problems but also anticipate future challenges. Through his dedication, he continues to inspire the next generation of engineers and scientists, fostering a more intelligent and sustainable world.