Compared with gravity data, gravity gradient data can reflect the structural features of density anomalies with higher sensitivity and resolution. Gravity gradient inversion is a common method for interpreting gravity gradient data, but the non-uniqueness of gravity gradient inversion solutions makes it difficult to quickly determine the effectiveness and reliability of the inversion results. To solve this problem, this paper combines the gravity gradient inversion and gravity gradient curvature methods and applies them to different sets of synthetic models. The gravity gradient inversion results are useful primarily for determining the spatial distributions and physical properties of density anomalies, while the gravity gradient curvature results have a prominent advantage in judging the geometric features of the density anomalies. In addition, one form of gravity gradient curvature, the contour lines of the shape index, can be compared with the top view of the inversion results to rapidly confirm the distribution of density anomalies, which is especially valuable for unexplored regions. On the basis of the respective advantages and features of these two methods, the gravity gradient curvature can be used as an important criterion to judge the results of gravity gradient inversion. The two methods are then combined to analyse airborne gravity gradient data measured in the field at the Kauring Test Site in Australia. Compared with the findings of previous gravity inversion research, this study shows that several anomalous blocks exist in the vicinity of the central anomalies, thereby demonstrating that the combination of these two methods is effective and reliable in identifying density anomalies.
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