Nonrepeatability effects on time-lapse 4D seismic full-waveform inversion for ocean-bottom node data

Abstract

Full-waveform inversion (FWI) can be applied to time-lapse (4D) seismic data for subsurface reservoir monitoring. However, nonrepeatability (NR) issues can contaminate the data and cause artifacts in the estimation of 4D rock and fluid property changes. Therefore, evaluating and studying the NR effects on the 4D data and FWI results can help, for instance, discriminate inversion artifacts from true changes and guide seismic survey design and processing workflows. Using realistic reservoir models, data, and field measurements of NR, we find the effects of NR source-receiver position and seawater velocity changes on the data and the 4D FWI results. We show that ignoring these NR effects in the inversion can cause strong artifacts in the estimated velocity change models and thus should be addressed before or during inversion. The NR source-receiver positioning issue can be successfully addressed by 4D FWI, whereas the NR water velocity issue requires measurements or estimations of water velocities. Furthermore, we compare the accuracy and robustness of the parallel, double-difference, and central-difference 4D FWI methods to realistic NR ocean-bottom node data in a quantitative way. Parallel 4D FWI fails to capture geomechanical changes and also overestimates the aquifer layer changes with NR data. Double-difference 4D FWI is capable of recovering the geomechanical changes, but it is also sensitive to NR noises, generating more artifacts in the overburden. By averaging the forward and reverse bootstrap 4D estimates, central-difference 4D FWI is more robust to NR noises and also produces the most accurate 4D estimates.