We developed a new strategy, based on graph theory concepts, to invert gravity data using an ensemble of simple point masses. Our method consisted of a genetic algorithm with elitism to generate a set of possible solutions. Each estimate was associated to a graph to solve the minimum spanning tree (MST) problem. To produce unique and stable estimates, we restricted the position of the point masses by minimizing the statistical variance of the distances of an MST jointly with the data-misfit function during the iterations of the genetic algorithm. Hence, the 3D spatial distribution of the point masses identified the skeleton of homogeneous gravity sources. In addition, our method also gave an estimation of the anomalous mass of the source. So, together with the anomalous mass, the skeleton could aid other 3D methods with promising geometric a priori parameters. Several tests with different values of regularizing parameter were made to bespeak this new regularizing strategy. The inversion results applied to noise-corrupted synthetic gravity data revealed that, regardless of promising starting models, the estimated distribution of point masses and the anomalous mass offered valuable information about the homogeneous sources in the subsurface. Tests on real data from a portion of Quadrilátero Ferrífero, Minas Gerais state, Brazil, were performed for complementary analysis of the proposed inversion method.

In this study, a least squares procedure for calculating the calibration constants of a portable gamma-ray spectrometer using the general inverse matrix method is presented. The procedure weights the model equations fitting to the calibration data, taking into account the variances in the counting rates and in the radioactive standard concentrations. The application of the described procedure is illustrated by calibrating twice the same gamma-ray spectrometer, with two independent data sets collected approximately 18 months apart in the same calibration facility.

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The use of airborne gravity gradiometry (AGG) has undergone rapid increase in mineral exploration in recent years. The performance and final results, however, are affected by many factors, including the acquisition system, acquisition parameters, quality control procedures, and the ruggedness of the terrain. We studied repeat surveys using 3D full tensor gradiometry and Falcon AGG systems under identical survey-design parameters over the Baú Mine Site, Quadrilátero Ferrífero, State of Minas Gerais, Brazil. We also evaluated the planning and quality control procedures adopted for acquisition through these systems. We also studied the results from the two systems in terms of signal-to-noise ratio, power spectral analysis, and correlation with the local geology. We aimed to evaluate the information from repeat surveys using identical parameters but different systems to facilitate the understanding of this new type of geophysical data and their application in mineral exploration.