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Abstract

Certain aspects provide a method for assigning a plurality of physical properties in space and time of a target underground region to a plurality of structural nodes defined for a first layer of a graph neural network machine learning model; constructing a regular grid from the plurality of structural nodes; generating, by a neural operator layer of the graph neural network machine learning model and using a fast Fourier transform, a neural operator output; projecting, by the neural operator layer via an inverse fast Fourier transform, the neural operator output onto the regular grid to generate an inverse grid; and generating a prediction from a second layer of the graph neural network machine learning model.

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First Claim