Full waveform inversion (FWI) has become a standard component of velocity model building workflows in marine exploration. In contrast, challenges such as poorer data quality, the presence of elastic effects and surface topography, have precluded the same integration from occurring for land exploration. In this study, we present one of the first applications of FWI to a land dataset from the western Canadian basin. We detail an end-to-end workflow that begins with data preprocessing and initial model building. The Cynthia 2D dataset is characterized by a lack of quality low-frequency information (below 8 Hz) and maximum offsets of 6.4 km. These properties limit the interrogation depth of conventional diving wave FWI. To counteract this, we devise two independent schemes for acoustic FWI. The first employs diving waves to update the near-surface (0.75 km maximum depth) P-wave velocity structure. The second uses reflection data to update structure to a maximum depth of 3 km. Both schemes employ multi-scale strategies, phase-based objective functions and gradient preconditioning to mitigate non-linearities in the inversion process. Standard quality control measures support the validity of the inverted models. The study provides a reference for future applications of FWI in the region.


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