• Title/Summary/Keyword: Computational Reconstruction

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Resolution and Image processing Methods of Tomogram and There impact of Computational Velocity Estimation (토모그램의 해상도와 영상처리 기법이 속도예측에 미치는 영향)

  • Lee, Min-Hui;Song, Da-Hee;Keehm, Young-Seuk
    • 한국지구물리탐사학회:학술대회논문집
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    • 2009.10a
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    • pp.147-154
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    • 2009
  • Physical properties of rocks, such as velocity, are strongly dependant on detailed pore structures, and recently, pore micro-structures by X-ray tomography techniques have been used to simulate and understand the physical properties. However, the smoothing effect during the tomographic reconstruction procedure often causes an artifact - overestimating the contact areas between grains. The pore nodes near a grain contact are affected by neighboring grain nodes, and are classified into grain nodes. By this artifact, the pore structure has higher contact areas between grains and thus higher velocity estimation than the true one. To reduce this artifact, we tried two image processing techniques - sharpening filter and neural network classification. Both methods gave noticeable improvement on contact areas between grains visually; however, the estimated velocities showed only incremental improvement. We then tried to change the resolutions of tomogram and quantify its impact on velocity estimation. The estimated velocity from the tomogram with higher spatial resolution was improved significantly, and with around 2 micron spatial resolution, the calculated velocity was very close to the lab measurement. In conclusion, the resolution of pore micro-structure is the most important parameter for accurate estimation of velocity using pore-scale simulation techniques. Also the estimation can be incrementally improved if combined with image processing techniques during the pore-grain classification.

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