Two-dimentional inversion of gravity data by defining primary points or strikes of an underground anomaly

Considering the development of different methods of modeling, the geophysicists are looking for methods that firstly can model the complex geological structures and secondly they are not time consuming. In this study, we aimed to model the gravity anomalies by defining the prior information. We studied a different method for interpreting 2D gravity anomalies produced by multiple and complex gravity sources separated from each other by short distances. This is an approach combining the best features of the automatic inversion and forward modeling. The assumed interpretation model is a grid of 2D prisms placed side by side; the density contrasts of this grid are the parameters to be determined. The interpreter designates the outlines of the gravity sources in terms of geometric elements (line segments and points) and the density contrast associated with the geometric elements defining each gravity source structure (this amounts to specifying the supposed density contrast for each source). The method then estimates the density-contrast distribution that fits the observed anomaly within the measurement errors and represents compact gravity sources closest to the specified geometric elements. The user can either accept the interpretation or adjust the gravity-source structure, changing the position of the geometric elements and/or the density contrast associated with each of the elements and begin the inversion once again. In fact,we estimate the geometrical shape of the underground anomalies. The interpreter defines some initial points and line segments with predefined density contrasts and then the modeling process estimates the final shape and density contrasts in the surrounding of the points and line segments. A computer code in MATLAB was written for these targets by the authors.
The advantage of this method was to hold the data fit bythe user.This capability helps the userconsiderthe noise existing in the data to achieve a more acceptable model.This was shown for synthetic models. Also, the method was tested on simple and complex synthetic models in two states, i.e. without noise and with random noise. Another advantage of this method was the ability of the inversion of complex geometric models andthe lack of sensitivity of the method to points and line segmentsplaced as the prior informationgiven.
Method’s practical application was shown by applying it to two sets of gravity data from different geologic settings. (1) Modeling a karstic cavity in the Havasan region in Ilam Province, Iran; (2) Modeling a Barite ore body in the Abadeh region in Fars Province, Iran. A Scintrex CG3 gravimeter with a sensitivity of 5 microGal was used for micro-gravity observations in the selected areas. Station altitudes were measured with a total station model Leica Tc 407 with an accuracy of 1-5mm in horizontal and vertical coordinates. The residual gravity grids were obtained using the Geosoft software.
For both regions, the forward modeling method was done. Then the inversion method (the method used in this study) was applied to the gravity data and compared with the forward modelingmethod. Indeed, this inversion method offered a better data fit and more acceptable model. When the user has information about approximate anomaly locations and density contrast, this method is one of the best choicesfor the 2D gravity modeling.