We have developed a level-set method for the inverse gravimetry problem of imaging salt structures with density contrast reversal. Under such a circumstance, a part of the salt structure contributes two completely opposite anomalies that counteract with each other, making it unobservable to the gravity data. As a consequence, this amplifies the inherent nonuniqueness of the inverse gravimetry problem so that it is much more challenging to recover the whole salt structure from the gravity data. To alleviate the severe nonuniqueness, it is reasonable to assume that the density contrast between the salt structure and the surrounding sedimentary host depends upon the depth only and is known a priori. Consequently, the original inverse gravity problem reduces to a domain inverse problem, where the supporting domain of the salt body becomes the only unknown. We have used a level-set function to parametrize the boundary of the salt body so that we reformulated the domain inverse problem into a nonlinear optimization problem for the level-set function, which was further solved for by a gradient descent method. Both 2D and 3D experiments on the SEG/EAGE salt model were carried out to demonstrate the effectiveness and efficiency of the new method. The algorithm was able to recover dipping flanks of the salt model, and it only took 40 min in a 2.5 GHz CPU to invert for a 3D model of 97,000 unknowns.
Memory efficient algorithm for solving the inverse gravimetry problem of finding several boundary surfaces in multilayered medium
