Japan Geoscience Union Meeting 2019

Presentation information

[J] Poster

M (Multidisciplinary and Interdisciplinary) » M-GI General Geosciences, Information Geosciences & Simulations

[M-GI33] Data-driven geosciences

Mon. May 27, 2019 1:45 PM - 3:15 PM Poster Hall (International Exhibition Hall8, Makuhari Messe)

convener:Tatsu Kuwatani(Japan Agency for Marine-Earth Science and Technology), Hiromichi Nagao(Earthquake Research Institute, The University of Tokyo), Kenta Ueki(Japan Agency for Marine-Earth Science and Technology), Masayuki Kano(Graduate school of science, Tohoku University)

[MGI33-P07] Data-driven estimation of material transfer from bulk compositions

*Tatsu Kuwatani1,2, Kenta Yoshida1, Kenta Ueki1, Ryosuke Oyanagi1, Masaoki Uno3, Shotaro Akaho4 (1.Japan Agency for Marine-Earth Science and Technology, 2.Japan Science and Technology Agency, 3.Graduate School of Environmental Studies, Tohoku University, 4.National Institute of Advanced Industrial Science and Technology)

Keywords:isocon, sparse modeling

Material transfer of elements is the most important consequences of geological processes. However, it is difficult to estimate it, even if both compositional datasets of before and after are available. This is because the compositional data are not absolute data but relative ratio data. Isocon analysis has been widely applied as a simple and powerful standard tool for quantitative estimation of material transfer to various geoscientific problems. Despite its powerfulness, the method needs to assume the reference frame such as immobile elements or conservation of mass or volume, which relies on the researchers’ intuition and experience. We propose a novel data-driven method which determines an appropriate reference frame from compositional data of multiple altered samples. In the proposed method, we use a mathematical framework, called sparse modeling, which can extract essential variables from high-dimensional datasets based on sparsity of the system. By optimizing the evaluation function, the least mobile elements are automatically selected. In this study, the effectiveness is validated and discussed using synthetic and natural sample data. The method seems to be a practical tool for estimate material transfer and it has the potential to be improved for particular problems due to its simple and flexible formulation.