Anna Suzuki

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Associate Professor

Tohoku University

Japan

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About

Anna Suzuki is an Associate Professor at Tohoku University in Japan. Her research focuses on geothermal systems, particularly utilizing physics-informed neural networks and machine learning for modeling geothermal reservoirs. She has contributed to recent articles concerning inverse modeling, automated parameter estimation, and the analysis of flow-channel structures in geothermal resource development.

Recent Grants

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Grant-in-Aid for Young Scientists (A)

Open Date: 2017-04-01

Close Date: 2019-03-01

Articles (12)

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2025

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2024

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2024

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2024

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2024

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2023

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2023

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2022

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2022

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2022

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2021

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2020

Collaborators (2)

Yosuke Kobayashi

Associate Professor

Muroran Institute of Technology

JAPAN

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Norihiro Watanabe

National Institute of Advanced Industrial Science and Technology

JAPAN

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Anna Suzuki

Research Interests

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About

Recent Grants

Articles (12)

Reliable and Practical Inverse Modeling of Natural‐State Geothermal Systems Using Physics‐Informed Neural Networks: Three‐Dimensional Model Construction and Assimilation With Magnetotelluric Data

Benchmark datasets of representative geothermal reservoir models with pseudo-geophysical exploration and well data

Automated parameter estimation for geothermal reservoir modeling using machine learning

Investigating rough single-fracture permeabilities with persistent homology

Modeling unobserved geothermal structures using a physics-informed neural network with transfer learning of prior knowledge

Analysis of large-scale performance with supercritical-water fracturing in geothermal resource development

Using 3D-printed fracture networks to obtain porosity, permeability, and tracer response datasets

Estimation of flow-channel structures with uncertainty quantification: Validation by 3D-printed fractures and field application

Data-Driven Geothermal Reservoir Modeling: Estimating Permeability Distributions by Machine Learning

On the maximum principle for the multi-term fractional transport equation

Bayesian and Neural Network Approaches to Estimate Deep Temperature Distribution for Assessing a Supercritical Geothermal System: Evaluation Using a Numerical Model

Experimental Study on Nano-/Microparticles Transport to Characterize Structures in Fractured Porous Media

Collaborators (2)

Yosuke Kobayashi

Norihiro Watanabe

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