Joint time-lapse full-waveform inversion with a time-lag cost function

Seismic time-lapse (4D) surveys have been widely used to quantitatively monitor the geophysical property changes within hydrocarbon reservoirs due to production effects. Full-waveform inversion (FWI), which has become one of the most reliable tools for velocity model building (VMB), is a natural technology choice for this purpose. However, robust reconstruction of time-lapse geophysical property changes within reservoirs using FWI remains challenging. Time-lapse signals are weak compared to the seismic response of the background model and thus vulnerable to noise and possible damage by data preprocessing. Imperfect repeatability of the baseline and monitor surveys also introduces uncertainties into the inverted time-lapse changes. To address these issues, we propose a 4D FWI approach, which jointly inverts both baseline and monitor data sets using a time-lag cost function with a target-oriented regularization scheme. This approach enhances the 4D signal within reservoirs while suppressing 4D noise away from them. We demonstrate our method using a synthetic and a field data example. We observe that it not only gives an interpretable 4D velocity difference, but also improves the 4D migration difference when compared with conventional 4D approaches.