| 研究課題/領域番号 |
21K13999
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| 研究種目 |
若手研究
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| 配分区分 | 基金 |
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| 審査区分 |
小区分17030:地球人間圏科学関連
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| 研究機関 | 東京工業大学 |
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研究代表者 |
パトモノアジ アニンディティヨ 東京工業大学, 工学院, JSPS特別研究員 (20899265)
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| 研究期間 (年度) |
2021-04-01 – 2023-03-31
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| 研究課題ステータス |
中途終了 (2022年度)
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| 配分額 *注記 |
4,680千円 (直接経費: 3,600千円、間接経費: 1,080千円)
2023年度: 910千円 (直接経費: 700千円、間接経費: 210千円)
2022年度: 650千円 (直接経費: 500千円、間接経費: 150千円)
2021年度: 3,120千円 (直接経費: 2,400千円、間接経費: 720千円)
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| キーワード | Porous media / Machine Learning / Pore throat network / 3D printer / Microtomography / Permeability |
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| 研究開始時の研究の概要 |
Nations around the globe had agreed to cut CO2 emission, but our society will still rely on hydrocarbon energy in the next decades. Coupling efficient petroleum production and CCS will provide a suitable alternative. Advancement in micro-tomography marks the rise of digital rock physics (DRP). In this decade, the implementations of machine learning (ML) to various industries have opened unprecedented possibilities. Here, I propose the implementation of ML with the combination between void structure images and statistics of pore-throat network by using deep learning (DL).
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| 研究実績の概要 |
Throughout this first year of research work, i have developed a method to incorporate 3D printer into this research work. By using the 3D printer, I have successfully fabricated a custom 2D micromodel. This fabrication model is low cost and very useful for rapid prototyping. This result was published in an academic paper this year. In addition, I have started 3D printing various granular particle that will be used for 3D porous media characterization.
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