Baehyun Min

Associate Professor

Ewha Womans University

South Korea

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About

Baehyun Min is an Associate Professor at Ewha Womans University in South Korea. His research focuses on topics including carbon capture and storage, machine learning applications in energy systems, and greenhouse gas emissions forecasting. He has contributed to several recent articles that discuss advanced modeling techniques for reservoir management and CO2 transportation systems. His work also explores the implications of hydrogen solubility for underground storage and the assessment of carbon markets in relation to environmental policies.

Articles (21)

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2025

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2021

Collaborators (4)

Changhyup Park

Changwon National University

SOUTH KOREA

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Minchul Jang

Ewha Womans University

SOUTH KOREA

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Won Suk Lee

Korea Institute of Geoscience and Mineral Resources

SOUTH KOREA

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kyungbook Lee

Kongju National University

SOUTH KOREA

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Baehyun Min

Research Interests

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About

Articles (21)

Stochastic forecasting of long-term greenhouse gas emissions and energy transitions: A comparative analysis of the US, EU, China, and Korea

History matching of a three dimensional channelized reservoir using a beta-convolutional variational autoencoder and ensemble smoother with multiple data assimilation

Modeling and Simulation of an Integrated CO2 Transport-Injection-Storage System for Geological Sequestration in a Depleted Gas Field

Effect of preprocessing on performances of machine learning-based mineral composition analysis on gas hydrate sediments, Ulleung Basin, East Sea

Analysis of Non-condensable Gas Injection Timing in eMSAGP Method for Oil Sands Reservoir with Thief Zone

Simulating and assessing carbon markets: Application to the Korean and the EU ETSs

Data-driven machine learning models for the prediction of hydrogen solubility in aqueous systems of varying salinity: Implications for underground hydrogen storage

Modeling a unified slug liquid holdup correlation based on a comprehensive analysis of entering bubble sharpness

Core-Scale Modeling and Simulation Study on Carbon Mineralization and Rock Property Changes Induced by CO2 Solution Injection into Basalt

Determination of Sequential Well Placements Using a Multi-Modal Convolutional Neural Network Integrated with Evolutionary Optimization

Design of Integrated CO2 Transportation-Injection-Storage System based on Multi-Objective Optimization

Machine-learning-based prediction of oil recovery factor for experimental CO2-Foam chemical EOR: Implications for carbon utilization projects

Numerical investigation of CO2-carbonated water-alternating-gas on enhanced oil recovery and geological carbon storage

Generation of High-Resolution Well Log Data by Using a Deep-Learning Algorithm

Generation of Synthetic Compressional Wave Velocity Based on Deep Learning: A Case Study of Ulleung Basin Gas Hydrate in the Republic of Korea

Efficient deep-learning-based history matching for fluvial channel reservoirs

Sequential short-term optimization of gas lift using linear programming: A case study of a mature oil field in Russia

Analysis of Data Disclosure and Reservoir Model of the Volve Oilfield in the North Sea

Prediction of Water Saturation from Well Log Data using Deep Learning Algorithms

A Review on Deep Learning Applications in Logging Data to Model Gas-Hydrate-Bearing Sediments

Optimization of Well Operations in a Carbonate Reservoir Using Stochastic Simplex Approximate Gradient

Collaborators (4)

Changhyup Park

Minchul Jang

Won Suk Lee

kyungbook Lee

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