Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Physics-Consistent Data-driven Waveform Inversion with Adaptive Data
  Augmentation   Seismic full-waveform inversion (FWI) is a nonlinear computational imaging
technique that can provide detailed estimates of subsurface geophysical
properties. Solving the FWI problem can be challenging due to its ill-posedness
and high computational cost. In this work, we develop a new hybrid
computational approach to solve FWI that combines physics-based models with
data-driven methodologies. In particular, we develop a data augmentation
strategy that can not only improve the representativity of the training set but
also incorporate important governing physics into the training process and
therefore improve the inversion accuracy. To validate the performance, we apply
our method to synthetic elastic seismic waveform data generated from a
subsurface geologic model built on a carbon sequestration site at Kimberlina,
California. We compare our physics-consistent data-driven inversion method to
both purely physics-based and purely data-driven approaches and observe that
our method yields higher accuracy and greater generalization ability.

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The categories of this paper are: atom-ph
7
The categories of this paper are: hep-th
2
The categories of this paper are: math
18
The categories of this paper are: econ
11
The categories of this paper are: hep-lat
0
The categories of this paper are: hep-ph
27
The categories of this paper are: comp-gas
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The categories of this paper are: alg-geom
24
The categories of this paper are: dg-ga
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The categories of this paper are: chem-ph
26
The categories of this paper are: bayes-an
6
The categories of this paper are: astro-ph
3
The categories of this paper are: physics
12
The categories of this paper are: nucl-th
4
The categories of this paper are: cond-mat
15
The categories of this paper are: nucl-ex