Acoustic full waveform inversion in time domain using blended data
He Liu, Daniel O. Trad, Kristopher A. H. Innanen
Cost is the primary factor that needs to be considered for the seismic data acquisition and processing. Super-shot or blended data strategy has been used in marine and land seismic surveys to reduce acquisition costs by reducing the number of recording times. Full waveform inversion (FWI) has been used to estimate high-resolution subsurface velocity models. However, it suffers from expensive computational cost for matching the synthetic and the observed data. Once the super-shots are acquired, conventional FWI methods would require a de-blending process for super-shots. To reduce the costs of both data acquisition and processing, FWI using blended data without the de-blending stage has been recognized very promising in future oil exploration. In this work, we accelerate the FWI process using different source-encoding strategies and compare their perfomance. The synthetic examples show that amplitude and random time delay encoding provide slow convergence rate and less satisfactory inversion results. The dynamic combined source-encoding strategy converges fast, providing updated velocity with ignorable artifacts. While the static combined source-encoding strategy provides the fast convergence rate as well as good estimation of velocity model. In addition, it requires the minimum computational cost since we can directly simulate the super-shots without the blending stage.