Multi-task unscented Kalman inversion (MUKI): a derivative-free joint inversion framework and its application to joint inversion of geophysic

Unscented Kalman inversion is a novel method that uses unscented Kalman filter to solve inverse problems. This paper applies it to inverse multiple geophysical observations simultaneously (i.e., Multi-task unscented Kalman inversion (MUKI)). In this method, the model parameters are updated iteratively in a derivative-free way, and a Gaussian approximation to the posterior distribution of the model parameters is obtained. We apply the MUKI to the joint inversion of receiver functions and surface wave dispersion. Synthetic and real data set tests have shown that MUKI recovers the model more efficiently (within O(10) iterations) than gradient-based methods and Markov chain Monte Carlo methods.