Gang Lei | Geological Engineering | Best Researcher Award

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🌟Prof. Gang Lei, Geological Engineering, Best Researcher Award🏆

Professor at China University of Geosciences, China

Gang Lei is a Professor in Geological Engineering at the China University of Geosciences. His expertise lies in petroleum engineering, particularly in areas such as fluid flow and transport in fractal media under stress conditions, multi-phase fluid flow in fractured-vuggy reservoirs, and percolation rules in tight sandstone gas reservoirs. With a strong background in mathematics and computational mathematics, Lei has contributed significantly to the understanding of complex fluid dynamics in porous media. He is skilled in utilizing various analytical and numerical modeling techniques to address challenges in reservoir engineering.

Author Metrics:

Scopus Profile

ORCID Profile

Google Scholar Profile

Gang Lei has an impressive publication record, with numerous papers published in refereed journals, including as the corresponding author. His research has been cited extensively, as evidenced by his Google Scholar profile. Lei’s work spans various topics in petroleum engineering, from theoretical analyses to experimental studies, demonstrating his versatility and depth of expertise in the field.

  • Citations: Lei Gang’s work has been cited 4,355 times across 3,593 documents.
  • Documents: Lei Gang has authored or co-authored 293 documents.
  • h-index: Lei Gang’s h-index, a measure of productivity and citation impact, is 29.

Education:

Lei’s academic journey began with a Bachelor’s degree in Mathematics and Applied Mathematics from China Agricultural University, followed by a Master’s degree in Computational Mathematics from China University of Petroleum-Beijing. He further pursued a Ph.D. in Petroleum Engineering at China University of Petroleum-Beijing, focusing on the study of percolation rules in tight sandstone gas reservoirs. Additionally, Lei completed post-doctoral research in Petroleum Engineering at Peking University and King Fahd University of Petroleum and Minerals, Saudi Arabia.

Research Focus:

Lei’s research primarily revolves around understanding fluid flow and transport phenomena in complex geological formations, particularly in porous and fractured media. His work includes investigating the behavior of multiphase fluids in fractured-vuggy reservoirs, analyzing stress-dependent permeability in porous media, and developing analytical models for various aspects of fluid dynamics under stress conditions. Lei’s research contributes to enhancing the understanding of reservoir behavior and optimizing strategies for oil and gas recovery.

Professional Journey:

Following his Ph.D., Lei embarked on a post-doctoral research journey, which included stints at Peking University and King Fahd University of Petroleum and Minerals, Saudi Arabia. Subsequently, he transitioned to his current position as a Professor in Geological Engineering at China University of Geosciences. Throughout his career, Lei has been actively involved in research, teaching, and professional service, contributing significantly to the field of petroleum engineering.

Honors & Awards:

Lei has received recognition for his academic achievements, including awards such as the Second Prize in the Paper Contest for the 5th Future Petroleum Engineers Forum and Enterprise First Scholarships for Doctor Candidates of China University of Petroleum-Beijing. His honors highlight his excellence in research and scholarly contributions to the field of petroleum engineering.

Publications Noted & Contributions:

Lei has made notable contributions to the petroleum engineering literature, with a prolific publication record comprising numerous papers in refereed journals, conference proceedings, and patents. His research covers a wide range of topics, including but not limited to, permeability prediction in fractured reservoirs, fluid flow in porous and fractured media under stress conditions, and modeling of multiphase flow phenomena. Lei’s publications reflect his deep expertise and significant contributions to advancing knowledge in petroleum engineering.

Title: Integrated Study on Carbon Dioxide Geological Sequestration and Gas Injection Huff-n-Puff to Enhance Shale Oil Recovery

  • Authors: L Wang, S Cai, W Chen, G Lei
  • Journal: Energies
  • Year: 2024
  • Summary: This study likely explores the combined approach of carbon dioxide geological sequestration and gas injection techniques (Huff-n-Puff) to enhance shale oil recovery, focusing on its feasibility, effectiveness, and potential environmental implications.

Title: A Novel Threshold Pressure Gradient Model and Its Influence on Production Simulation for Shale Oil Reservoirs

  • Authors: J Qu, Z Tang, G Lei, Q Wu, Q Liao, F Ning
  • Journal: Energy & Fuels
  • Year: 2024
  • Summary: This paper may introduce a new model for threshold pressure gradient in shale oil reservoirs and discuss its impact on production simulation. It likely addresses the complexities of fluid flow in shale formations and its implications for reservoir management.

Title: Super-resolution reconstruction of 3D digital rocks by deep neural networks

  • Authors: S You, Q Liao, Z Yan, G Li, S Tian, X Song, H Wang, L Xue, G Lei, X Liu, …
  • Journal: Geoenergy Science and Engineering
  • Year: 2024
  • Summary: This study might present a method for super-resolution reconstruction of 3D digital rock images using deep neural networks. It could focus on improving the resolution and quality of digital rock models for better characterization of reservoir properties.

Title: Estimation of heat transfer and thermal conductivity of particle-reinforced hollow cylinder composites

  • Authors: G Zhang, L Zhang, G Lei, Y Gao
  • Journal: Mechanics of Advanced Materials and Structures
  • Year: 2024
  • Summary: This paper may discuss the estimation of heat transfer and thermal conductivity properties of particle-reinforced hollow cylinder composites. It could be relevant for understanding the thermal behavior of composite materials in various engineering applications.

Title: Experimental study on dual benefits of improvement of CO2 enhanced oil recovery and its storage capacity for depleted carbonate oil reservoirs

  • Authors: X Zhou, W Yu, G Lei, SZ Khan, R Al-Abdrabainabi, MS Kamal, YS Wu
  • Journal: Advances in Geo-Energy Research
  • Year: 2024
  • Summary: This study likely presents experimental findings on the benefits of CO2 enhanced oil recovery and its potential for carbon storage in depleted carbonate oil reservoirs. It could explore the synergies between enhanced oil recovery techniques and carbon capture and storage initiatives.

Research Timeline:

Lei’s research journey has been marked by a series of impactful projects and collaborations. From his early work on evaluating ultralow permeability reservoirs during CO2 flooding to his recent investigations into stress-dependent permeability in fractured-vuggy reservoirs, Lei’s research timeline showcases a progression of expertise and innovation in petroleum engineering. His projects have encompassed both experimental and theoretical approaches, contributing to advancements in reservoir characterization and enhanced oil recovery strategies.

Collaborations and Projects:

Throughout his career, Lei has collaborated on various research projects with institutions and organizations both domestically and internationally. These collaborations have enabled him to tackle complex challenges in petroleum engineering, ranging from reservoir characterization to fluid flow modeling in porous and fractured media. Lei’s involvement in projects such as studying multiphase pseudo relative permeability and analyzing key technologies for enhanced oil recovery underscores his interdisciplinary approach and commitment to addressing industry-relevant problems.

Byung Kwan Oh | Structural engineering | Best Researcher Award

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🌟Assist Prof Dr. Byung Kwan Oh, Structural engineering, Best Researcher Award 🏆

Assistant Professor at Yonsei University, South Korea

Byung Kwan Oh, Ph.D., is an accomplished Assistant Professor in the Department of Architecture and Architectural Engineering at Yonsei University. With a rich academic background in structural engineering, Byung Kwan focuses on innovative research areas such as artificial intelligence-based safety evaluation for buildings and multi-objective structural design. His expertise lies in structural health monitoring, seismic retrofitting, and sustainable design methodologies. Byung Kwan’s dedication to advancing knowledge in these fields is evident through his extensive publication record and active involvement in academia.

Author Metrics:

Byung Kwan Oh’s impact as a researcher is evidenced by his author metrics, including citation counts, h-index, and other measures of scholarly influence. His research publications have garnered attention from peers and experts in the field, demonstrating the significance and relevance of his work in advancing structural engineering practices.

Orcid Profile

Google Scholar Profile

Scopus Profile

Byung Kwan Oh is affiliated with Yonsei University in Seoul, South Korea. He has a Scopus Author Identifier with the ID 56134318500. Byung Kwan Oh has an ORCID profile with the ID 0000-0002-7422-2947. According to Scopus, he has 1,222 citations from 975 documents. Byung Kwan Oh has authored 53 documents and has an h-index of 22.

Education:

Byung Kwan Oh pursued his educational journey at Yonsei University in South Korea. He earned his Bachelor of Science in Architectural Engineering followed by a Master of Science and a Ph.D. in Structural Engineering. His doctoral thesis focused on modal influence-based system identification and sustainable structural health monitoring for buildings, showcasing his commitment to advancing structural engineering practices.

Research Focus:

Byung Kwan Oh’s research interests revolve around two main areas: artificial intelligence-based safety evaluation for buildings and multi-objective structural design. He utilizes cutting-edge techniques such as deep learning for damage detection, structural dynamics analysis, and optimization algorithms for seismic retrofitting and sustainable design. His work aims to enhance the safety, efficiency, and sustainability of building structures through innovative methodologies and technologies.

Professional Journey:

Byung Kwan Oh has built a diverse professional journey encompassing academic, research, and practical experiences. From his early days as an Associate Engineer at Posco E&C to his tenure as a Visiting Post-Doctoral Research Associate at Princeton University, he has gained valuable insights into various aspects of structural engineering. He has held positions as a Research Professor, Post-Doctoral Fellow, Lecturer, and Assistant Professor at esteemed institutions in South Korea and the United States, contributing significantly to both education and research in his field.

Honors & Awards:

Throughout his career, Byung Kwan Oh has been recognized for his outstanding contributions to structural engineering. His notable achievements include awards for his research publications, exemplary teaching performance, and impactful contributions to the field. These honors underscore his dedication to excellence and his significant impact on the academic and professional community.

Publications Top Noted & Contributions:

Byung Kwan Oh’s contributions to the field of structural engineering are reflected in his extensive publication record. He has authored numerous research papers, book chapters, and conference presentations that have advanced knowledge in structural health monitoring, seismic retrofitting, and sustainable design. His work has been widely cited and has made significant contributions to the academic discourse in his field.

“Evolutionary learning based sustainable strain sensing model for structural health monitoring of high-rise buildings” (2017, Applied Soft Computing):

  • Authors: BK Oh, KJ Kim, Y Kim, HS Park, H Adeli
  • Presents a sustainable strain sensing model for monitoring the structural health of high-rise buildings.
  • Utilizes evolutionary learning techniques to develop an efficient and sustainable approach to strain sensing.

“Convolutional neural network‐based wind‐induced response estimation model for tall buildings” (2019, Computer-Aided Civil and Infrastructure Engineering):

  • Authors: BK Oh, B Glisic, Y Kim, HS Park
  • Introduces a model for estimating wind-induced responses in tall buildings.
  • Utilizes convolutional neural networks (CNNs) to improve the accuracy and efficiency of response predictions.

“Vision-based system identification technique for building structures using a motion capture system” (2015, Journal of Sound and Vibration):

  • Authors: BK Oh, JW Hwang, Y Kim, T Cho, HS Park
  • Discusses a vision-based technique for identifying system properties of building structures.
  • Uses a motion capture system to gather visual data and analyze it for structural parameter identification.

“Real-time structural health monitoring of a supertall building under construction based on visual modal identification strategy” (2018, Automation in Construction):

  • Authors: HS Park, BK Oh
  • Describes a real-time structural health monitoring system for a supertall building under construction.
  • Utilizes a visual modal identification strategy to assess the building’s health and integrity during construction.

“Convolutional neural network–based data recovery method for structural health monitoring” (Structural Health Monitoring):

  • Authors: BK Oh, B Glisic, Y Kim, HS Park
  • Introduces a method for recovering missing or corrupted data in structural health monitoring systems.
  • Utilizes convolutional neural networks (CNNs) to reconstruct missing data, enhancing monitoring reliability.

Research Timeline:

Byung Kwan Oh’s research journey spans over a decade, beginning with his doctoral studies at Yonsei University and continuing through his various academic and research positions. His timeline reflects a progression from foundational research in structural dynamics and health monitoring to more advanced studies in artificial intelligence-based safety evaluation and multi-objective structural design. Each phase of his research journey has contributed to the evolution of his expertise and the advancement of knowledge in his field.