Integrating multiscale parameters information into 3D stochastic magnetic anomaly inversion

Abstract

We present a 3D stochastic inversion method based on the geostatistical approach of cokriging for inversion of magnetic anomaly data on multiple scale parameters using borehole and surface data to limit the resulting solution space. Recovering susceptibilities in 3D magnetic anomaly inversion requires integration of many different data. These data mainly come from different sources with different volume supports (point and block support). The presented algorithm has the capability of inverting data on multiple supports using downscaling and upscaling. Borehole susceptibilities (point support) are up-scaled to block susceptibilities where some of them are selected as constraints. The block constraints are used in magnetic anomaly inversion and, finally, the inverted susceptibilities are down-scaled to small prisms. Two modes of application are presented: estimation and simulation. The method is first applied to a synthetic stochastic model. The results of downscaling and upscaling show the ability of the method to invert surface and borehole data simultaneously on multiple scale parameters. The results also clearly show the significant role of borehole data in improving depth resolution. Finally, a case study using susceptibility measurements collected on outcrops and on numerous borehole cores at the Perseverance mine (Quebec, Canada) is presented. The information from the recovered 3D model are useful in analyzing the geology of massive sulfide for the domain under study. It also shows that the addition of constraints at different scales helps in delineating bodies, which would have been missed by only using the magnetic anomaly data.