Neural operators, as a powerful approximation to the non-linear operators between infinite-dimensional function spaces, have proved to be promising in accelerating the solution of partial differential ...

Abstract: Physics-informed neural networks (PINNs) have recently been utilized to tackle wave equation-based forward and inverse problems. However, they encounter challenges in accurately predicting ...

In the context of the rapid development of computer hardware and the continuous improvement of the artificial intelligence and deep learning theory, aiming at the traditional numerical solution method ...

Abstract: The accurate characterization of elastic properties near boreholes is critical for reservoir evaluation, well integrity assessment, and high-resolution formation imaging. Traditional ...

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