Forward Modeling Research of Gravity Data Offset in North China Region

Due to the complexity and overlap effects of gravity anomalies, the gravity high point always deviates from the real position of the target. Researching the offset characteristics is helpful to determine the right location of gravity anomalies. In this paper, a series of forward models were designed to calculate the offset features under different assumptions. Different density models were established based on the measured gravity data in north China Sunhu area and a variety of methods were tried to eliminate offset effects under different conditions. The results indicate that the gravity anomalies of different density bodies can be separated effectively and the real position of target can be correctly located by using the “layer stripping method”.

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Forced Neural Network (FNN) model

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Overview of the data sets used for joint inversion. (a) Map view of the

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Schematic diagram of model I.

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Modelled zero offset seismic section for the start of the simulation

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Comparison of the numerical free streamline shape with the exact

The original and processed gravity responses of model III.

Histogram of generalization errors for different structures, all