Compression of seismic forward modeling wavefield using TuckerMPI.

With the increasing use of seismic waveform inversion and imaging, the scale of numerical simulations of seismic waves has been increasing. Concomitantly, the resulting extremely large amounts of seismic data being produced are causing storage, reading, and processing difficulties. Data compression, especially lossy compression, can reduce the data storage requirement. In this study, we apply TuckerMPI, a recently developed lossy large-scale data compression tool, in seismic forward modeling, and compare TuckerMPI with ZFP, SZ2, SZ3, DCTZ, and TTHRESH on compression ratio, accuracy, compression and decompression times. Using TuckerMPI to accelerate seismic waveform inversion has also been studied. Instead of using the waveform difference with/without compression as an acceptable criterion, we focus on the influence of compression on the sensitivity kernels calculated using the 4D wavefields. Especially, we quantitatively investigate the allowed relative error level that does not significantly affect the results of the waveform inversion. Numerical experiments show that TuckerMPI can reduce the file size by 1000+ fold while the inversion result is similar to that using the raw fields.