Design of Sustainable Geo-Energy Systems
Geothermal power generation can be carried out more sustainably by creating a recirculation operation in which water used for power generation is returned to the subsurface. The effectiveness of different recirculation strategies depends on the subsurface structure and flow connectivity between the wells that return fluid to the subsurface and the wells that produce hot geothermal fluid for power generation. In this study, we are developing methods for estimating the subsurface structure and well connectivity using results of tracer tests for flow evaluation and for optimally designing a sustainable water recirculation operation. This includes proposing new tracer testing methods using nano- and microparticles. Our optimization and estimation workflows incorporate tracer and thermal transport modeling, quantitative evaluation of uncertainty, model error estimation, and machine learning.
Quantitative evaluation of uncertainty
Collaborator: Bjarkason (Suzuki Lab)
To get the data directly from the basement, you need to dig a well, which is very expensive.
Therefore, it is necessary to analyze based on limited data and insufficient data.
The information used (measurement data and model) is expressed numerically as to how certain or not it is, and how much the uncertainty affects future prediction is evaluated.
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Bjarkason et al. (2020), Proc AFI
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Bjarkason and Suzuki (2019), Proc 16th ICFD
Particle tracer flow experiment in rock structure
Collaborator: Nakayama (Tooku Univ., Watanabe Lab)
By using nano-microparticles for flow assessment in underground cracks, it may be possible to obtain information that was not previously available.
In this research, we will understand how water flows through the rock by creating a microstructure of the rock on the tracer silicon substrate and visualizing the contents.
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Suzuki et al. (2020), Rock Mech. Rock Eng.
