The invention relates to a physical-data-driven sequence type seismic oscillation generation method. The method comprises the following steps: acquiring a historical seismic
record; constructing a main earthquake
ground motion random field model based on the physical mechanism of the
ground motion field; the physical mechanism comprises a seismic source, a propagation path and a local
site model; obtaining main earthquake parameters based on historical earthquake records according to the main earthquake
ground motion random field model; the main earthquake parameter is used for predicting an unknown main earthquake seismic
record according to a main earthquake seismic oscillation random field model to obtain a main earthquake seismic oscillation
time history; and constructing an
aftershock seismic oscillation generation model based on a conditional
generative adversarial network model according to the main seismic oscillation
time history to realize prediction of a seismic oscillation field. According to the method, the parameters of the main earthquake are generated based on the earthquake
motion field of the physical mechanism, the
time history of the main earthquake is obtained, the
aftershock prediction model is constructed according to the conditional
generative adversarial network, the physical mechanism model is combined with
artificial intelligence, the
model prediction fitness and accuracy are improved, the
aftershock is predicted, the prediction effect is improved,
complex calculation is avoided, and the model construction efficiency is improved.