2D inverse modeling of the gravity field due to a chromite deposit using the Marquardt’s algorithm and forced neural network

Abstract

In this paper, two modeling method are employed. First, a method based on the Marquardt’salgorithm is presented to invert the gravity anomaly due to a finite vertical cylinder source. Theinversion outputs are the depth to top and bottom, and radius parameters. Second, Forced NeuralNetworks (FNN) for interpreting the gravity field as try to fit the computed gravity in accordancewith the estimated subsurface density distribution to the observed gravity. To evaluate the ability ofthe methods, those are employed for analyzing the gravity anomalies from assumed models withdifferent initial parameters as the satisfactory results were achieved. We have also applied theseapproaches for inverse modeling the gravity anomaly due to a Chromite deposit mass, situated eastof Sabzevar, Iran. The interpretation of the real gravity data using both methods yielded almost thesame results.