Open GGOOAI 开源项目Seismic-Velocity-Inversion
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Deep learning system for seismic velocity inversion using a SincNet-GAT-UNet architecture, physics-informed temporal encoding, graph attention fusion, and FiLM-conditioned spatial prediction
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The model processes 5 shot gathers per sample (10,001 time steps across 31 receivers each) and outputs a full 300 x 1,259 subsurface velocity field. The champion configuration achieves **~0.0655% MAPE** on the held-out evaluation set.
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