3D elastic multisource full waveform inversion on distributed GPU clusters

Abstract

Full-waveform inversion (FWI) serves as a useful tool to quantitatively investigate the properties of the media. One of the greatest challenges is its enormous computational cost, especially for the three-dimensional (3D) case. The multisource encoding strategy is a crucial method to speed up FWI. However, current 3D elastic FWI algorithms with the simultaneous sources, such as random time series and random polarity methods, may be subjected to the crosstalk noise, which severely degrades inversion quality. We present a novel 3D elastic crosstalk-free multisource full-waveform inversion method (MFWI). The encoded sources with a series of single-frequency components are excited to perform the seismic wavefield simulation. Extracting the wavefield corresponding to each single-frequency harmonic source by phase-sensitive detection (PSD) algorithm, the multisource wavefield can be decomposed. Therefore, summing the gradients with respect to the model parameters of all decomposed single frequencies can effectively avoid the crosstalk in our MFWI algorithm. Furthermore, to increase the practicability and universality of the algorithm, we adopt the graphic processing unit (GPU) based on the domain decomposition to improve the MFWI algorithm. The multi-scale strategy with a flexible encoding number in each scale helps to enhance the robustness of our algorithm. The numerical examples demonstrate that our method can achieve domain decomposition simulation and obtain 3D crosstalk-free multisource elastic wave inversion results.