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Abstract

Disclosed are a method, system, and device for full waveform inversion on elastic wave seismic data. The method includes: constructing a convolutional neural network full waveform inversion module; determining a multi-scale inversion frequency based on the observation data; performing low-pass filtering on the observation data; determining an initial velocity and an RTM image corresponding to the current inversion frequency; determining a current inversion result by using the convolutional neural network full waveform inversion module based on the initial velocity and the RTM image corresponding to the current inversion frequency; determining whether inversion performed at the multi-scale inversion frequency is completed; if the inversion is not completed, performing inversion on a next frequency, performing smoothing processing on the inversion result, and replacing the initial velocity corresponding to the current inversion frequency with an inversion result obtained after smoothing processing until the inversion performed at the multi-scale inversion frequency is completed.

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First Claim