reference model

Summary Nowadays attempts to detect and achieve buried structures and underground resources have developed widely and geophysics is a means of identifying these structures. One of the main goals of geophysical data interpretations, is to incorporate additional information to the process of inversion in order to define the characteristics of geological structures as precisely as possible. In this paper, a three-dimensional (3-D) constrained inversion of gravity data acquired from Qom salt dome using Grav3D program is presented, and then, the results are compared with the results of 3-D constrained inversion of the data using constraints including smoothness, positivity, reference model and bounded model. For testing the algorithm, a step by step constraint inversion including smoothness, positivity, reference model and bounded model has been performed on an artificial model, and then, the algorithm has been used for modeling the gravity data acquired from Qom salt dome.
Introduction The recent ability to produce 3-D models of the sub-surface, coupled with an increasing need to explore concealed resources, results from geophysical inversions that provide more and more significant information to the explorers. Since our country is rich in mineral resources, the use of optimized modern and efficient methods to prevent additional costs in exploring these resources is very important. Thus, in the first step of this exploration procedure, we should try to collect as much information as possible about the underground structures. In this direction, 3-D modeling of geophysical data can lead to successfully interpreting the data. The outcome of modeling is to have a better understanding of target such as the shape and depth of source. Finding these specifications of the source directly influences the subsequent decisions for management of major costs.
Methodology and Approaches The inversion method, used in this paper, is based on the inversion algorithm developed by Li and Oldenburg. As a result of inversion of gravity data, the geometry of source or anomaly and also density contrast between the anomaly and the background are determined. In the inversion algorithm used in this research, the earth is modeled using a large number of rectangular cells of constant density, and the final density distribution is obtained by minimizing a model objective function subject to fitting the observed data. The model objective function has the flexibility to incorporate prior information, and thus, the constructed model not only fits the data but also agrees with additional geophysical and geological constraints. A depth weighting is applied in the objective function to counteract the natural decay of the kernels so that the inversion yields depth information. Incorporating additional information to the process of inversion is the strength of this algorithm which can be done with different constraints such as smoothness, positivity, reference model and bounded model. Constrained modeling leads inversion towards the production of logical models and as a result, the validity and reliability of the final model will increase.
Results and Conclusions For optimized use of the algorithm, at first, it has been tested on synthetic models in which the synthetic gravity data have been contaminated with noise. Then, according to the accommodation of the results with the right model, the algorithm has been used for inversion of real gravity data, acquired from Qom salt dome, and then, the final results have been visualized. The inversion results indicate that Qom salt dome has lengthened to the depth of at least 4500 meters beneath the earth surface.