Gravity inversion with a binary structure constraint imposed by magnetotelluric data and its application to a Carlin-type gold deposit

With characteristics of low cost and high efficiency, the gravity method is one of the most important means for the deep exploration of mineral resources. However, due to its inherent physical properties, its inversion results provide a limited vertical resolution. To reduce the uncertainty of gravity inversion, it is necessary to impose constraints from other geophysical methods, drilling, or geologic models. Based on the high vertical resolution of the multifrequency magnetotelluric (MT) data, we have developed a novel 2D gravity inversion method with a binary structure constraint imposed by MT data. The guided model is the density model reconstructed by the cross-gradient joint inversion of MT and gravity data, and the target and background regions of the guided model are divided using a fuzzy c-means clustering algorithm. The obtained binary target-background model is used as a structural constraint of the gravity inversion. The gravity inversion changes the density values of the target region rather than the background region, which can significantly reduce the dimensions of the inversion solution equation. The experimental results demonstrate that, even if the resistivity model and the density model indicate an inconsistent structure, the binary structure-constrained gravity inversion can reconstruct the density model with a higher degree of resolution than the traditional gravity inversion and cross-gradient joint inversion. Finally, we apply this algorithm to density modeling for the exploration of Carlin-type gold deposits in the southeast of the Jilin province, China, where the image determines the distribution of deep Paleoproterozoic Formation and high-density deposits, providing important technical support for the exploration of Carlin-type gold deposits.