Soon Jee Seol

757 total citations
81 papers, 559 citations indexed

About

Soon Jee Seol is a scholar working on Geophysics, Ocean Engineering and Mechanical Engineering. According to data from OpenAlex, Soon Jee Seol has authored 81 papers receiving a total of 559 indexed citations (citations by other indexed papers that have themselves been cited), including 75 papers in Geophysics, 53 papers in Ocean Engineering and 16 papers in Mechanical Engineering. Recurrent topics in Soon Jee Seol's work include Seismic Imaging and Inversion Techniques (53 papers), Seismic Waves and Analysis (45 papers) and Geophysical Methods and Applications (41 papers). Soon Jee Seol is often cited by papers focused on Seismic Imaging and Inversion Techniques (53 papers), Seismic Waves and Analysis (45 papers) and Geophysical Methods and Applications (41 papers). Soon Jee Seol collaborates with scholars based in South Korea, United States and Japan. Soon Jee Seol's co-authors include Joongmoo Byun, Daeung Yoon, Seogi Kang, Jiho Park, Jung Ho Kim, Myeong‐Jong Yi, Jungho Kim, Yoonho Song, Seunghwan Chung and Jihun Choi and has published in prestigious journals such as IEEE Transactions on Geoscience and Remote Sensing, Geophysics and Geophysical Journal International.

In The Last Decade

Soon Jee Seol

71 papers receiving 541 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Soon Jee Seol South Korea 14 498 376 82 75 38 81 559
Daniele Colombo United States 16 811 1.6× 484 1.3× 62 0.8× 96 1.3× 19 0.5× 90 866
Ketil Hokstad Norway 12 522 1.0× 305 0.8× 123 1.5× 28 0.4× 26 0.7× 63 592
Christopher L. Liner United States 14 434 0.9× 291 0.8× 112 1.4× 28 0.4× 32 0.8× 67 493
E. Stucchi Italy 14 562 1.1× 203 0.5× 58 0.7× 53 0.7× 14 0.4× 71 611
Aldo Vesnaver Italy 12 537 1.1× 273 0.7× 65 0.8× 44 0.6× 49 1.3× 81 606
Yi-an Cui China 12 274 0.6× 211 0.6× 78 1.0× 44 0.6× 37 1.0× 55 377
P. Thore France 14 635 1.3× 546 1.5× 237 2.9× 102 1.4× 37 1.0× 62 848
Ed Kragh Norway 13 604 1.2× 304 0.8× 128 1.6× 72 1.0× 47 1.2× 33 683
Daeung Yoon South Korea 11 264 0.5× 310 0.8× 151 1.8× 67 0.9× 16 0.4× 33 436
Paolo Dell’Aversana Italy 10 856 1.7× 424 1.1× 148 1.8× 53 0.7× 16 0.4× 62 915

Countries citing papers authored by Soon Jee Seol

Since Specialization
Citations

This map shows the geographic impact of Soon Jee Seol's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Soon Jee Seol with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Soon Jee Seol more than expected).

Fields of papers citing papers by Soon Jee Seol

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Soon Jee Seol. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Soon Jee Seol. The network helps show where Soon Jee Seol may publish in the future.

Co-authorship network of co-authors of Soon Jee Seol

This figure shows the co-authorship network connecting the top 25 collaborators of Soon Jee Seol. A scholar is included among the top collaborators of Soon Jee Seol based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Soon Jee Seol. Soon Jee Seol is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Park, Jiho, et al.. (2025). Improving generalization performance of deep learning–based seismic data interpolation. Geophysical Prospecting. 73(5). 1534–1551.
2.
Park, Jiho, et al.. (2024). Machine learning-based time-lapse 1D seismic full-waveform inversion with efficient training data generation in a carbon capture and storage monitoring. Geoenergy Science and Engineering. 238. 212852–212852. 3 indexed citations
4.
Seol, Soon Jee, et al.. (2023). Deep-learning-based airborne transient electromagnetic inversion providing the depth of investigation. Geophysics. 89(2). E31–E45. 3 indexed citations
5.
Seol, Soon Jee, et al.. (2023). Interpretation of Frequency-Domain Airborne Electromagnetic Data Based on the Deep Neural Network Incorporating Topographic Information. IEEE Transactions on Geoscience and Remote Sensing. 61. 1–14. 4 indexed citations
6.
Seol, Soon Jee, et al.. (2022). Seismic Data Interpolation Using Attention-Based Deep Learning. 83rd EAGE Annual Conference & Exhibition. 1–5. 1 indexed citations
7.
Park, Jiho, Jihun Choi, Soon Jee Seol, Joongmoo Byun, & Young Kim. (2021). A method for adequate selection of training data sets to reconstruct seismic data using a convolutional U-Net. Geophysics. 86(5). V375–V388. 19 indexed citations
8.
Seol, Soon Jee, et al.. (2021). Imaging subsurface orebodies with airborne electromagnetic data using a recurrent neural network. Geophysics. 86(6). E407–E419. 17 indexed citations
9.
Seol, Soon Jee, et al.. (2021). Deep learning spectral enhancement considering features of seismic field data. Geophysics. 86(5). V389–V408. 12 indexed citations
10.
Seol, Soon Jee, et al.. (2021). Extraction of diffractions from seismic data using convolutional U-net and transfer learning. Geophysics. 87(2). V117–V129. 19 indexed citations
11.
Byun, Joongmoo, et al.. (2017). Efficient Structure-Oriented Filter-Edge Preserving (SOF-EP) Method using the Corner Response. Geophysics and Geophysical Exploration. 20(3). 176–184. 1 indexed citations
12.
Seol, Soon Jee, et al.. (2015). Interpretation of controlled-source electromagnetic data from iron ores under rough topography. Journal of Applied Geophysics. 124. 106–116. 4 indexed citations
13.
Kang, Seogi, Soon Jee Seol, & Joongmoo Byun. (2012). A feasibility study of CO2 sequestration monitoring using the mCSEM method at a deep brine aquifer in a shallow sea. Geophysics. 77(2). E117–E126. 26 indexed citations
14.
Byun, Joongmoo, et al.. (2010). Study on Microseismic Monitoring Method for Enhanced Oil Recovery (EOR). Journal of the Korean Society of Mineral and Energy Resources Engineers. 47(6). 871–879. 1 indexed citations
15.
Seol, Soon Jee, et al.. (2010). An Investigation in Operating and Design Parameters for Gas Hydrate Exploration using Marine CSEM. Journal of the Korean Society of Mineral and Energy Resources Engineers. 47(2). 139–150. 1 indexed citations
16.
Seol, Soon Jee, et al.. (2010). Crosswell monitoring using virtual sources and horizontal wells. Geophysics. 75(3). SA37–SA43. 14 indexed citations
17.
Byun, Joongmoo, et al.. (2009). Effective monitoring for CO 2 sequestration with virtual sources. The Royal Society of Chemistry’s Journals, Books and Databases (The Royal Society of Chemistry). 3855–3859. 1 indexed citations
18.
Kim, Jungho, et al.. (2007). Application of Geophysical Methods to the Safety Analysis of an Earth Dam. Journal of Environmental and Engineering Geophysics. 12(2). 221–235. 47 indexed citations
19.
Seol, Soon Jee, et al.. (2004). A Radar Survey at a Granite Quarry to Delineate Fractures and Estimate Fracture Density. Journal of Environmental and Engineering Geophysics. 9(2). 53–62. 7 indexed citations
20.
Seol, Soon Jee, Jung Hee Suh, Yoonho Song, Hee Joon Kim, & Ki Ha Lee. (2002). The potential of fracture imaging using high-frequency, single-hole electromagnetic data. Geophysics. 67(4). 1087–1094. 2 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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