3D correlation imaging of the vertical gradient of gravity data

We present a new 3D correlation imaging approach for vertical gradient of gravity data for deriving a 3D equivalent mass distribution in the subsurface. In this approach, we divide the subsurface space into a 3D regular grid, and then at each grid node calculate a cross correlation between the vertical gradient of the observed gravity data and the theoretical gravity vertical gradient due to a point mass source. The resultant correlation coefficients are used to describe the equivalent mass distribution in a probability sense. We simulate a geological syncline model intruded by a dike and later broken by two vertical faults. The vertical gradient of gravity anomaly of the model is calculated and used to test the approach. The results demonstrate that the equivalent mass distribution derived by the approach reflects the basic geological structures of the model. We also test the approach on the transformed vertical gradient of real Bouguer gravity data from a geothermal survey area in Northern China. The thermal reservoirs are located in the lower portion of the sedimentary basin. From the resultant equivalent mass distribution, we produce the depth distribution of the bottom interface of the basin and predict possible hidden faults present in the basin