Abstract:

To improve the gravity data processing quality and reduce the impact of super-thick ice sheet on gravity data interpretation, it is important to separate the gravity anomalies caused by ice sheet from the superimposed anomalies. To address this problem, we establish two continental polar ice structural models and simulate the Bouguer gravity anomalies of these models. Subsequently, three separation methods (i.e., polynomial fitting, upward continuation, and preferential filtering) are used to extract the ice sheet-related gravity anomalies. Based on the results, the application effects of different separation methods are compared and analyzed. Our results demonstrate that the polynomial fitting method is effective when the density interface fluctuation is relatively gentle, but artificial anomalies are easily introduced when the interface fluctuates greatly. The upward continuation method works well in discriminating anomalies caused by shallower sources. However, due to the greater depth of the polar model and unreasonable continuation height selection, insufficient separation occurs in the test. The preferential filtering method yields better separation result for the complex model, but its performance depends greatly on the frequency band selection. Therefore, when stripping the gravity anomalies caused by polar ice sheet, due to the complex geological conditions (e.g., thickness and fluctuation of polar ice sheets), available geological and geophysical materials should be adopted to determine the appropriate separation method for specific conditions.

Key words: polar ice sheet, potential field separation, polynomial fitting method, upward continuation, preferential filtering