{'fraction_non_alphanumeric': 0.04125950054288816, 'fraction_numerical': 0.0, 'mean_word_length': 5.9547169811320755, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Parameterization analysis and field validation of VTI-elastic full-waveform inversion in a walk-away vertical seismic profile configuration

Elastic full-waveform inversion (FWI) in transversely isotropic media with a vertical symmetry axis (VTI) is applied to field walk-away vertical seismic profile (W-VSP) data acquired in Western Canada. The performance of VTI-elastic FWI is significantly influenced by the model parameterization choice. Synthetic analysis based on specific field survey configuration is carried out to evaluate three different VTI-elastic model parameterizations. Interparameter trade-offs are quantified using the recently introduced interparameter contamination sensitivity kernel approach. Synthetic results suggest that neglecting anisotropy leads to inaccurate velocity estimations. For the conventional vertical velocity-Thomsen’s parameter parameterization (i.e., vertical P-wave velocity, vertical S-wave velocity, Thomsen’s parameters [Formula: see text] and [Formula: see text]), a sequential inversion strategy is designed to reduce strong natural interparameter trade-offs. The model parameterizations of elastic-constant ([Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text]) and velocity-based (vertical, horizontal, and normal move-out P-wave velocities and vertical S-wave velocity) models appear to suffer from fewer interparameter trade-offs, providing more reliable velocity and anisotropy models. Results derived from application of VTI-elastic FWI to the field W-VSP data set tend to support the synthetic conclusions. Multiparameter point spread functions are calculated to quantify the local interparameter trade-offs of the inverted models. The output inversion results are interpreted to provide valuable references regarding the target hydrocarbon reservoir.