PINNslope: Seismic data interpolation and local slope estimation with physics informed neural networks
Francesco Brandolin,
Matteo Ravasi,
Tariq Alkhalifah
Abstract:Interpolation of aliased seismic data constitutes a key step in a seismic processing workflow to obtain high-quality velocity models and seismic images. Building on the idea of describing seismic wavefields as a superposition of local plane waves, we propose to interpolate seismic data by using a physics informed neural network (PINN). In the proposed framework, two feed-forward neural networks are jointly trained using the local plane wave differential equation as well as the available data as two terms in th… Show more
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