Posted by Yanhua Liu

Figure 1: Inverted V_P0 produced by the conventional L₂-norm FWI using actual wavelet (upper) and distorted wavelet (down). 

Time-lapse full-waveform inversion can provide high-resolution information about changes in the reservoir properties during hydrocarbon production and CO2 injection. However, the accuracy of the estimated source wavelet, which is critically important for time-lapse FWI, is often insufficient for field-data applications. The error in the source wavelet hinders the matching between the observed and simulated and distorts the inversion results (see Fig 1).

The so-called “source-independent” FWI is designed to reduce the influence of the source wavelet on the inversion results. We incorporate the convolution-based source-independent technique into a time-lapse FWI algorithm for VTI (transversely isotropic with a vertical symmetry axis) media. The algorithm is tested on a model with a graben structure and the modified VTI Marmousi model using three time-lapse strategies (the parallel-difference, sequential-difference, and double-difference methods). The results confirm the ability of the developed methodology to reconstruct the localized time-lapse parameter variations even for a strongly distorted source wavelet (see Fig 2 and 3). The algorithm remains robust in the presence of moderate noise in the input data but the accuracy of the estimated time-lapse changes depends on the model complexity. More detailed can be found in our paper published on Geophysics (https://library.seg.org/doi/full/10.1190/geo2021-0306.1).

Figure 2: Inverted V_P0 produced by the conventional L₂-norm FWI using actual wavelet (left) and proposed source-independent FWI algorithm with the distorted wavelet (right). 

Figure 3: Time-lapse variations of V_P0 produced by the proposed source-independent FWI algorithm with the distorted wavelet using: (a) parallel-difference method, (b) sequential-difference method, and (c) double-difference method.