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Minhui Lee

Researcher at Kongju National University

Publications -  6
Citations -  982

Minhui Lee is an academic researcher from Kongju National University. The author has contributed to research in topics: Smoothing & Relative permeability. The author has an hindex of 4, co-authored 6 publications receiving 793 citations.

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Digital rock physics benchmarks-Part I: Imaging and segmentation

TL;DR: The goal is to explore and record the variability of the computed effective properties as a function of using different tools and workflows, and benchmarking is the topic of the two present companion papers.
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Digital rock physics benchmarks-part II: Computing effective properties

TL;DR: This analysis provides the DRP community with a range of possible outcomes which can be expected depending on the solver and its setup, and falls within the ranges consistent with the relevant laboratory data.
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Assessment and Calibration of Ultrasonic Velocity Measurement for Estimating the Weathering Index of Stone Cultural Heritage

TL;DR: In this article, the authors measured the ultrasonic velocities of the same type of rock and found that the difference of ultrasonic velocity between fresh rock and weathered rock indicates the degree of weathering.
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Quantitative analysis of resolution and smoothing effects of digital pore microstructures on numerical velocity estimation

TL;DR: In this paper, the errors in seismic velocity by resolution and smoothing of pore geometry using three samples: an unconsolidated sand pack and two medium-porosity sandstones with different degrees of consolidation, and they concluded that the resolution should be considered in the first place when obtaining digital pore microstructures to minimize errors in velocity estimation.

Smoothing Effect in X-ray Microtomogram and Its Influence on the Physical Property Estimation of Rocks

TL;DR: In this paper, the smoothing effect during tomographic inversion creates artifacts in pore micro-structures and causes inaccurate property estimation, and to mitigate this artifact, they tried to use sharpening filter and neural network classification techniques.