Observation Site Selection for Physical Model Parameter Estimation toward Process-Driven Seismic Wavefield Reconstruction
Kumi Nakai, Takayuki Nagata, Keigo Yamada, Yuji Saito, Taku Nonomura,, Masayuki Kano, Shin-ichi Ito, and Hiromichi Nagao

TL;DR
This paper introduces a method for selecting optimal seismic observation sites to accurately estimate physical model parameters, enabling efficient seismic wavefield reconstruction with reduced data and computational costs.
Contribution
It proposes a sensitivity-based site selection method using the D-optimality criterion for process-driven seismic wavefield reconstruction.
Findings
The method effectively identifies observation sites for accurate parameter estimation.
Seismic wavefield reconstruction accuracy improves with the selected sites.
Sensitivity analysis of physical parameters enhances site selection strategy.
Abstract
The ``big'' seismic data not only acquired by seismometers but also acquired by vibrometers installed in buildings and infrastructure and accelerometers installed in smartphones will be certainly utilized for seismic research in the near future. Since it is impractical to utilize all the seismic big data in terms of the computational cost, methods which can select observation sites depending on the purpose are indispensable. We propose an observation site selection method for the accurate reconstruction of the seismic wavefield by process-driven approaches. The proposed method selects observation sites suitable for accurately estimating physical model parameters such as subsurface structures and source information to be input into a numerical simulation of the seismic wavefield. The seismic wavefield is reconstructed by the numerical simulation using the parameters estimated based on…
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Taxonomy
TopicsSeismic Imaging and Inversion Techniques · Reservoir Engineering and Simulation Methods
