Reflection traveltime inversion (RTI) plays an important role in the realm of exploration geophysics due to its ability to restore long-wavelength subsurface structures. However, due to the necessary migration/demigration process, every iteration of RTI requires six times as many forward calculations, resulting in high computational and storage costs. High-performance computing can accelerate RTI calculations, but it has little effect on the consumption of large storage volumes. Thus, the background and perturbed wavefields with excitation approximation are used in RTI to overcome the storage issue. In the authors’ RTI, the strategies of source-wavelet convolution and wavefield direction decomposition are introduced to solve the problems of missing source signature and multipathing in the excitation approximation wavefields. Numerical examples have demonstrated that excitation approximation RTI can provide an accurate background velocity model and reduce the storage burden of RTI.

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