Simultaneous determination of multiple physical parameters using full-waveform inversion (FWI) suffers from interparameter trade-off difficulties. Analyzing the interparameter trade-offs in different model parameterizations of isotropic-elastic FWI, and thus determining the appropriate model parameterization, are critical for efficient inversion and obtaining reliable inverted models. Five different model parameterizations are considered and compared including velocity-density, modulus-density, impedance-density, and two velocity-impedance parameterizations. The scattering radiation patterns are first used for interparameter trade-off analysis. Furthermore, a new framework is developed to evaluate the interparameter trade-off based upon multiparameter Hessian-vector products: Multiparameter point spread functions (MPSFs) and interparameter contamination sensitivity kernels (ICSKs), which provide quantitative, second-order measurements of the interparameter contaminations. In the numerical experiments, the interparameter trade-offs in various model parameterizations are evaluated using the MPSFs and ICSKs. Inversion experiments are carried out with simple Gaussian-anomaly models and a complex Marmousi model. Overall, the parameterization of the P-wave velocity, S-wave velocity, and density, and the parameterization of the P-wave velocity, S-wave velocity, and S-wave impedance perform best for reconstructing all of the physical parameters. Isotropic-elastic FWI of the Hussar low-frequency data set with various model parameterizations verifies our conclusions.

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