Abstract
Joint inversion of surface wave and gravity data can reduce non-uniqueness of individual inversion and has been applied in the research of the crust and lithospheric mantle. Direct parameter coupling is mainly used for jointly inverting the both dataset in the current research, which need specifying a function relationship between shear wave (S-wave) velocity and density. It can result in spurious features when the models violate the parameter relationship. Moreover, deriving an appropriate velocity-density function is difficult and a single physical property relationship may not always be suitable for all regions. In this study, we present a new joint inversion algorithm for ambient noise surface wave and gravity data with variation of information (VI) coupling. The correlation between S-wave velocity and density models is constructed by a one-to-one relationship with VI. The effectiveness of the algorithm is verified using the synthetic and field data. The results of synthetic examples indicate that density anomalies have been recovered accurately by the joint inversion, but they are almost not imaged by the individual inversion. S-wave velocity models recovered by the joint inversion are more accurate than that from the individual inversion. And the fitting parameter relationship of the joint inversion models is closer to the true model than individual inversion. In the field case from the southeast of Tibetan Plateau, the S-wave velocity model of joint inversion has a higher resolution than separate inversion. Density model recovered by the joint inversion clearly displays crustal structures, which have been severely distorted in the individual inversion model. Joint inversion with VI coupling is an effective and valuable approach for inverting surface wave and gravity data.