Daniela Andrea Arias Ortiz | Big Data Analytics | Best Researcher Award

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Dr. Daniela Andrea Arias Ortiz | Big Data Analytics | Best Researcher Award

KAUST| Saudi Arabia

Author Profile

DANIELA A. ARIAS ORTIZ | PETROLEUM ENGINEER 👩‍🔬💡

📚 EARLY ACADEMIC PURSUITS

DANIELA A. ARIAS ORTIZ embarked on her academic journey in Petroleum Engineering with a strong foundation from the National University of Colombia, Medellin, where she completed her BSc in 2017 with a GPA of 4.3/5. Her undergraduate work focused on complex geomechanical challenges and reservoir simulations, paving the way for her future studies. Daniela then pursued her MSc and PhD at King Abdullah University of Science and Technology (KAUST), Saudi Arabia, specializing in Energy Resources and Petroleum Engineering. She demonstrated her academic excellence through her notable thesis work on shale reservoir simulation and later her PhD dissertation, which focused on physics-based and data-driven production forecasting.

🧪 PROFESSIONAL ENDEAVORS

Daniela’s career took a decisive turn when she interned with Saudi Aramco at both the Remote Fields Gas Production Engineering Department and the Unconventional Department. These roles provided practical exposure to unconventional reservoir simulation, production data analysis, and hydraulic fracturing techniques. Additionally, she gained experience in reservoir engineering with Equion-Energia-Limited, Colombia, where she contributed to evaluating the productivity of fractured wells through advanced simulation methods.

🔬 CONTRIBUTIONS AND RESEARCH FOCUS ON Big Data Analytics 

Daniela’s research centers on unconventional reservoir simulation, shale oil, and shale gas, with a specific focus on multi-stage hydraulic fracturing design and production data analysis. Her work has led to significant insights into rate transient analysis and the impact of fracture geometries on reservoir performance. She has pioneered methods to predict ultimate recovery from hydraulically fractured shale gas wells, contributing to more accurate forecasting and enhancing the recovery rates from shale formations.

🌍 IMPACT AND INFLUENCE

Daniela’s research has influenced both academia and industry by introducing innovative models for shale reservoir production forecasting. Her contributions have been recognized at various international conferences such as the SPE Annual Technical Conference and Exhibition and Interpore 2023. Her studies on fracture propagation and hydraulic fracturing have shaped current understandings of the energy transition and the optimization of unconventional resources.

📈 ACADEMIC CITATIONS AND PUBLICATIONS

Daniela has published several influential papers, including works presented at conferences like the SPE Annual Technical Conference and International Petroleum Technology Conference. Some of her key publications include:

  • The Impact of Stimulation Treatment Size on Ultimate Recovery from Hydraulically Fractured Shale Gas Wells (2022)
  • Validation and Analysis of the Physics-Based Scaling Curve Method for Ultimate Recovery Prediction in Hydraulically Fractured Shale Gas Wells (2022)
  • The Effect of Hydraulic Fracture Geometry on Well Productivity in Shale Oil Plays with High Pore Pressure (2021)

These publications are essential for advancing understanding in shale gas production and contribute to ongoing research in unconventional energy resources.

🏅 HONORS & AWARDS

  • Dean’s Award for Academic Excellence (2024 & 2023, KAUST)
  • SPE KAUST Student Chapter Presidential Award for outstanding student chapter (2023)
  • Second Place in Middle East Region Petrobowl (2019)
  • Outstanding Contribution to Student Life at KAUST (2023)

🌐 LEGACY AND FUTURE CONTRIBUTIONS

Looking forward, Daniela aims to continue her research into data-driven production forecasting and hydraulic fracture modeling to further optimize unconventional energy extraction. Her legacy will likely shape the future of energy sustainability, ensuring efficient and environmentally responsible production methods in the petroleum industry.

🌠 FINAL NOTE

Daniela A. Arias Ortiz is a brilliant Petroleum Engineer whose work on unconventional reservoirs has transformed the way the industry views hydraulic fracturing and shale oil/gas production. Her pursuit of innovation in shale reservoir simulation and rate transient analysis has positioned her as a promising leader in energy research.

📑 NOTABLE PUBLICATIONS 

Physics-based, data-driven production forecasting in the Utica and Point Pleasant Formation
  • Authors: Daniela Arias-Ortiz, Tadeusz W. Patzek
  • Journal: Geoenergy Science and Engineering
  • Year: 2025-03
Forecasts and Uncertainty Quantification of Oil and Gas Production from Shales
The Impact of Stimulation Treatment Size on Ultimate Recovery From the Hydraulically Fractured Shale Gas Wells
Validation and Analysis of the Physics-Based Scaling Curve Method for Ultimate Recovery Prediction in Hydraulically Fractured Shale Gas Wells
The Effect of Hydraulic Fracture Geometry on Well Productivity in Shale Oil Plays with High Pore Pressure
  • Journal: Energies
  • Year: 2021
  • HANDLE: 10754/673713
Shale Reservoir Simulation in Basins with High Pore Pressure and Small Differential Stress

 

Moncef Soualhi – Aéronautique – International Data Mastery Achievement Award 

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Mr. Moncef Soualhi - Aéronautique - International Data Mastery Achievement Award 

Universelle de Franche Comté - France

Author Profile

Early Academic Pursuits

Mr. Moncef Soualhi's academic journey began with a strong foundation in electrical engineering. He pursued his Bachelor's degree in Technology with a focus on electrotechnics at the Université Ferhat Abbas Sétif 1. This provided him with essential theoretical knowledge and practical skills in electrical systems.

Following his undergraduate studies, Soualhi continued to excel academically by enrolling in a Master's program in Electrotechnics, specializing in industrial electrotechnics at the same university. During this time, he undertook a significant internship at the Laboratory of Signal Analysis and Industrial Processes (LASPI) in France. This experience exposed him to real-world applications of his field of study, particularly in the area of fault detection and diagnosis in electromechanical systems.

Professional Endeavors

Mr. Soualhi's professional journey is marked by a diverse range of experiences across multiple continents. He embarked on his doctoral research journey at the Institut National Polytechnique de Toulouse (INPT), focusing on intelligent monitoring and failure prognostics of industrial systems. This research was funded by the Interreg Poctefa program, highlighting the relevance and importance of his work in the European context.

Throughout his doctoral studies, Soualhi engaged in collaborative research efforts with prestigious institutions and organizations, including the École Polytechnique Montréal and CanmetÉNERGIE in Canada. These collaborations enabled him to explore new avenues in failure prognostics, such as predicting long-term fouling in the pulp industry and estimating cleaning times for heat exchanger tubes.

Additionally, Soualhi's involvement with Metallicadour, a center for technology transfer and resources, allowed him to delve into the study of tool fatigue in robotic machining systems. His contributions in this area led to the development of robust health indicators for monitoring and diagnosing tool defects, showcasing his interdisciplinary approach to problem-solving.

Contributions and Research Focus On Aéronautique

Mr. Soualhi's research focus lies at the intersection of data-driven prognostics, fault detection, and machine learning for industrial systems. He has made significant contributions to the development of intelligent monitoring techniques, particularly in the areas of feature extraction, health indicator construction, and fusion of heterogeneous data sources.

His research outputs include publications in renowned journals and presentations at prestigious conferences, underscoring the academic rigor and relevance of his work. By addressing complex challenges in various industries, including robotics, energy, and manufacturing, Soualhi has demonstrated the practical applicability of his research outcomes.

Accolades and Recognition

Mr. Soualhi's academic achievements and contributions have been acknowledged through various accolades and recognition. Notably, he successfully defended his doctoral thesis, earning him the prestigious title of Doctor in Automatics and Industrial Engineering from the Institut National Polytechnique de Toulouse. Additionally, his publications in esteemed journals and conferences reflect the high quality and impact of his research in the scientific community.

Impact and Influence

Mr. Soualhi's research has the potential to significantly impact the fields of industrial automation, predictive maintenance, and reliability engineering. By developing advanced prognostic techniques and intelligent monitoring systems, he aims to enhance the operational efficiency, safety, and sustainability of industrial processes across diverse sectors.

Furthermore, Soualhi's collaborative efforts with international partners and active involvement in academic forums have facilitated knowledge exchange and dissemination, contributing to the global advancement of research in his field.

Legacy and Future Contributions

As Soualhi continues to advance in his academic and professional journey, his legacy is poised to be characterized by innovation, excellence, and meaningful impact. His ongoing research endeavors seek to address emerging challenges in industrial systems, paving the way for more efficient, reliable, and sustainable operations.

In the future, Soualhi's contributions are expected to extend beyond the realm of academia, influencing industry practices and shaping the next generation of researchers and practitioners in the field of automatics, industrial engineering, and data-driven prognostics.

Citations

A total of 183 citations for his publications, demonstrating the impact and recognition of her research within the academic community.

  • Citations    183
  • h-index       6
  • i10-index    5

Notable Publication