OpenFWI: Benchmark Seismic Datasets for Machine Learning-Based Full Waveform Inversion
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We present OpenFWI, a collection of large-scale open-source benchmark datasets for seismic full waveform inversion (FWI). OpenFWI is the first-of-its-kind in the geoscience and machine learning community to facilitate diversified, rigorous, and reproducible research on machine learning-based FWI. OpenFWI includes datasets of multiple scales, encompasses diverse domains, and covers various levels of model complexity. Along with the dataset, we also perform an empirical study on each dataset with a fully-convolutional deep learning model. OpenFWI has been meticulously maintained and will be regularly updated with new data and experimental results. We appreciate the inputs from the community to help us further improve OpenFWI. At the current version, we publish seven datasets in OpenFWI, of which one is specified for 3D FWI and the rest are for 2D scenarios. All datasets and related information can be accessed through our website at https://openfwi.github.io/.
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