3D stochastic joint inversion of gravity and magnetic data

A novel stochastic joint inversion method based on cokriging is applied to estimate density and magnetic susceptibility distributions from gravity and total magnetic field data. The method fully integrates the physical relations between density–gravity, on one hand, and magnetic susceptibility–total magnetic field, on the other hand. As a consequence, when the data are considered noise-free, the responses from the inverted density and susceptibility data exactly reproduce the observed data. The required density and magnetic susceptibility auto- and cross covariance are assumed to follow a linear model of coregionalization (LCM). The parameters of the LCM are estimated from v–v plot fitting of the gravity and total magnetic experimental covariances. The model is tested on two synthetic cases and one real data set, the Perseverance mine (Quebec, Canada). Joint inversions are compared to separate inversions. The joint inversions better recover the known models in the synthetic cases. With the real data set, better definition and location of the mineralized lenses are achieved by joint inversion.

► A novel stochastic joint inversion method based on cokriging is introduced.
► The method is applied to estimate density and susceptibility distributions.
► Linear coregionalization model (LCM) is used to obtain required covariances.
► The method is tested on two synthetic cases, compact and stochastic model.
► A real case study at the Perseverance mine (Quebec, Canada) is presented.