2023 Fiscal Year Final Research Report
Verification of the indeces of high CO2 concentration detection in a natural CO2 leakage sea and its implementation in ecosystem model
| Project/Area Number |
21H01539
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Review Section |
Basic Section 24020:Marine engineering-related
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| Research Institution | The University of Tokyo |
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Principal Investigator |
Sato Toru 東京大学, 大学院新領域創成科学研究科, 教授 (30282677)
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| Co-Investigator(Kenkyū-buntansha) |
下島 公紀 東京海洋大学, 学術研究院, 教授 (70371490)
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| Project Period (FY) |
2021-04-01 – 2024-03-31
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| Keywords | CCS / CO2海中漏洩 / 海水中CO2濃度 / 海洋調査 / 溶存酸素 / 機械学習 |
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| Outline of Final Research Achievements |
Offshore CO2 storage requires monitoring of seawater CO2 concentration in case of unexpected leaks. However, since CO2 concentration is affected by biological activities such as photosynthesis, an index is needed to distinguish leakage from natural fluctuations. In 2021 and 2020, CO2 concentrations were observed in concentric circles around the leakage point in the natural CO2 leakage area of Tachibana Bay, Nagasaki Prefecture and the artificial leak off the coast of Tateyama. As a result, false negatives caused by natural fluctuations due to leakage could be avoided. We also developed a method of the optimal placement of observation points using an inverse method that accurately estimates a leak location from observation point information. In 2020, we developed a machine learning method that learned the CO2 concentration off Tateyama and analyzed seawater data from other areas to determine leakage, and were able to obtain appropriate results.
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| Free Research Field |
海洋環境工学
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| Academic Significance and Societal Importance of the Research Achievements |
理論上、相関が高い指標は漏洩を自然変動と誤判断する確率を減らすことが可能なはずである。ただし、提案する高相関指標を含む複数指標を用いて、海底下に貯留したCO2の予期せぬ漏洩を検出するためには、それを実証する必要があった。この研究では、自然CO2漏出海域にて、新たな指標を併用する手法が、高精度に擬陽性のみならず偽陰性を回避できることを確認した。さらに、機械学習法を用いることで、科学的根拠のない閾値を用いることなく、漏出と自然変動を識別することができた。これは海底下CO2貯留事業において、高コストの再調査の頻度を格段に下げるという社会的なニーズも非常に高い成果と言える。
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