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Slides for my talk at EAGE 2019 in London this June. We attempt to extrapolate for missing low-frequency content in seismic data using a deep learning (DL) approach. We generate a set of random subsurface models and use those to produce a synthetic training dataset. We train a supervised DL model to infer a mono-frequency representation of a common shot gather, given respective data on multiple high frequencies. In the end, we show an example of FWI on extrapolated synthetic data and an example of bandwidth extrapolation on a single shot from field data.