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Dr. Hanjoon Park | Seismic exploration | Best Researcher Award

Post-doctoral Researcher at Research Institute of Energy and Resources, Seoul National University, South Korea.

Dr. Hanjoon Park is a dedicated researcher and geophysicist with expertise in seismic data processing, machine learning, and energy systems engineering. He completed his Ph.D. in Geophysics and Energy Systems Engineering at Seoul National University, where his doctoral research focused on self-supervised learning-based seismic interpolation techniques. With a strong background in Python, Fortran, and Matlab, Dr. Park has developed innovative seismic imaging algorithms and contributed to projects supported by the Korean government for carbon capture and storage (CCS) and geophysical exploration. As a post-doctoral researcher at Seoul National University’s Research Institute of Energy and Resources, he continues to advance his research in distributed acoustic sensing (DAS) modeling and full waveform inversion (FWI) for geological storage and monitoring survey applications. Dr. Park’s commitment to scientific excellence and interdisciplinary collaboration underscores his contributions to the field of geophysics.

Professional Profiles:

Education

Dr. Hanjoon Park earned his Ph.D. in Geophysics, Energy Systems Engineering from Seoul National University, Korea, completing his dissertation on “Self-supervised learning-based seismic interpolation technique using spectrum suppression through GFKI and masked UNet” from Mar. 2020 to Feb. 2024. Prior to his doctoral studies, he obtained a B.S. in Energy and Resources Engineering with top honors from the same institution, spanning Mar. 2016 to Feb. 2020.

Professional Experience

Dr. Hanjoon Park boasts a rich professional journey in geophysics and energy systems engineering. He currently serves as a Post-doctoral Researcher and Geophysicist at Seoul National University’s Research Institute of Energy and Resources, focusing on modeling and full waveform inversion (FWI) for distributed acoustic sensing (DAS) and participating in government-supported projects for carbon capture and storage (CCS). Prior to this role, Dr. Park worked as a Full-time Researcher at the Geophysical Prospecting Lab, also at Seoul National University. During this time, he delved into machine learning-based seismic data processing and imaging techniques, contributing significantly to advancements in seismic trace interpolation, noise attenuation, and 4D noise suppression. His expertise extends to conventional seismic data processing methods, where he developed various techniques using Python, Fortran, and Matlab. Dr. Park’s research endeavors have been instrumental in enhancing our understanding of geophysical exploration and its applications, particularly in the context of CCS monitoring.

Research Interest

Dr. Hanjoon Park’s research interests revolve around cutting-edge developments in geophysical exploration and energy systems engineering. His primary focus lies in the development of distributed acoustic sensing (DAS) modeling and full waveform inversion (FWI) techniques for geological storage and monitoring surveys. Additionally, he is deeply engaged in advancing machine learning-based DAS processing and imaging methods, aiming to revolutionize data analysis in the field of geophysics. Dr. Park is also dedicated to exploring innovative monitoring techniques for high-level radioactive waste facilities, contributing to the safe and sustainable management of nuclear energy resources.

Award and Honors

Dr. Hanjoon Park has received prestigious recognition for his contributions to the field of geophysics and energy systems engineering. Notably, he was honored with the Student Paper Presenter Award at the 2022 Fall Conference of the Korean Society of Earth and Exploration Geophysicists. Additionally, Dr. Park has been the recipient of esteemed fellowships, including the Fellowship for Fundamental Academic Fields in 2022 and the Presidential Science Scholarship from 2016 to 2019. These awards and fellowships underscore his commitment to academic excellence and innovation in his research endeavors.

Research Skills

Dr. Hanjoon Park possesses a diverse set of research skills that enable him to excel in the field of geophysics and energy systems engineering. He is proficient in the development of advanced seismic data processing and imaging techniques using machine learning algorithms, Python, Fortran, and Matlab. His expertise includes seismic trace interpolation, ambient noise attenuation, ground-roll attenuation, 4D noise suppression, FX deconvolution, frequency filtering, curvelet-based seismic interpolation, spectral balancing, amplitude balancing, and least square reverse time migration. Dr. Park also has experience in modeling and full waveform inversion (FWI) for distributed acoustic sensing (DAS), particularly focusing on geological storage and monitoring survey applications. His research skills enable him to contribute significantly to projects related to carbon capture and storage (CCS) and geophysical exploration, supported by the Korean government and other institutions.

Publications

  1. Ground-roll attenuation using dual-model self-supervised selective learning with blind horizontal convolutional neural networks
    • Authors: Son, Y.H., Park, H., Cho, Y., Min, D.-J.
    • Year: 2024
    • Citations: 0
  2. U-Net++ Based Subshallow Gas-Scattered Image Conditioning: Small-Scale Case Study of Seismic Data Acquired in the Korean East Sea
    • Authors: Lee, J., Lee, M.J., Park, H., Jun, H., Cho, Y.
    • Year: 2024
    • Citations: 0
  3. Improvement of Spectrum Suppression-Based Deep Learning Interpolation Technique
    • Authors: Park, H., Lee, J.-W., Min, D.-J.
    • Year: 2023
    • Citations: 1
  4. RECONSTRUCTION OF MISSING SEISMIC DATA USING COARSE REFINE NETWORK WITH UPSAMPLING AND F-K LOSS
    • Authors: Park, H., Lee, J., Min, D.
    • Year: 2022
    • Citations: 0
  5. Coarse-Refine Network With Upsampling Techniques and Fourier Loss for the Reconstruction of Missing Seismic Data
    • Authors: Park, H., Lee, J.-W., Hwang, J., Min, D.-J.
    • Year: 2022
    • Citations: 2
Hanjoon Park | Seismic exploration | Best Researcher Award

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