Imaging Methods Versus Inverse Methods: An Option or An Alternative?

Both imaging and inversion of potential fields allow the estimation of the source-property distribution. Here, we compare these methods in order to assess their relative advantages and performances. Specifically, we use an iterative imaging algorithm, which is based on the compact depth from extreme points (CDEXP), and the data-space inverse algorithm. This choice was determined because both the methods use a depth weighting function and a compacting function, i.e., they yield a compact source solution. Inverted and imaged solutions are compared with each other, for two sets of noise-corrupted synthetic data, one relative to a simple prism and the other to two oppositely dipping dikes. In both cases, the two models show a noticeable similarity. However, the execution times are substantially different, with the inversion times being an order of magnitude greater. Finally, we interpret two real gravity data sets by using both the approaches: gravity data sets acquired over 1) the Galinge iron-ore deposit of Northwest China and 2) Jiaodong gold deposit of East China. We found that the source models obtained by imaging and inversion methods are once again similar