• 235 Citations
  • 8 h-Index
19972019
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Fingerprint Fingerprint is based on mining the text of the experts' scientific documents to create an index of weighted terms, which defines the key subjects of each individual researcher.

seismic data Earth & Environmental Sciences
inversions Physics & Astronomy
carbon sequestration Earth & Environmental Sciences
well Earth & Environmental Sciences
gas hydrate Earth & Environmental Sciences
electromagnetism Physics & Astronomy
monitoring Earth & Environmental Sciences
interpolation Earth & Environmental Sciences

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Research Output 1997 2019

A structure-tensor-constrained cooperative inversion using an extracted physical property distribution

Kim, B., Seol, S. J., Byun, J. & Cho, S., 2019 Feb 6, In : Geophysical Journal International. 217, 2, p. 1334-1352 19 p.

Research output: Contribution to journalArticleResearchpeer-review

Open Access
Tensors
Physical properties
physical property
physical properties
tensors

Automatic labeling strategy in semi-supervised seismic facies classification by integrating well logs and seismic data

Lee, S., Choi, J., Yoon, D. & Byun, J., 2019 Jan 1, p. 2166-2170. 5 p.

Research output: Contribution to conferencePaperResearchpeer-review

learning
marking
seismic data
well
impedance

Integrated inversion of the quantitative seismic interpretation result and electromagnetic data using structure tensor

Kim, B., Byun, J. & Oh, S., 2019 Jan 1, 24th European Meeting of Environmental and Engineering Geophysics. European Association of Geoscientists and Engineers, EAGE, (24th European Meeting of Environmental and Engineering Geophysics).

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

Tensors
inversion

Location-based parameterization of CSEM data inversion for the monitoring of hydraulic fracturing with magnetically enhanced proppants

Noh, K., Lee, K. H., Oh, S., Seol, S. J. & Byun, J., 2019 Jan 1, p. 924-928. 5 p.

Research output: Contribution to conferencePaperResearchpeer-review

data inversion
fracturing
parameterization
hydraulics
inversions

Salt Delineation from Electromagnetic Data Using Convolutional Neural Networks

Oh, S., Noh, K., Yoon, D., Seol, S. J. & Byun, J., 2019 Apr 1, In : IEEE Geoscience and Remote Sensing Letters. 16, 4, 8527527.

Research output: Contribution to journalArticleResearchpeer-review

electrical resistivity
Salts
salt
Neural networks
hydrocarbon reservoir