Edge Detection in Potential Fields Using Optimal Auto‐Ratios of Vertical Gradients

Derivative calculation of potential-fields is widely used in edge detection of geologic bodies. However, the traditional gradient methods are susceptible to noise disturbance, and can lead to instability of results. Besides, the edges of small-sized geologic bodies are difficult to be detected because of superimposed anomalies. In this paper, we give the definition of auto-ratios and present a new method for edge detection by using optimal auto-ratios of vertical derivatives, and elaborate mathematical implication and physical meaning of this method. The model test shows that the method using optimal auto-ratios of vertical gradients can greatly suppress noise disturbance and accurately detect the edges of geologic bodies which cannot be recognized by traditional edge detection methods. In application, we choose gravity data of the Yalujiang Basin where geological conditions are very complex to test the optimal auto-ratio method. The results show that the tectonic boundaries recognized by the optimal auto-ratios of the third-order vertical derivatives correspond well to distribution characteristics of real geologic bodies, which are in agreement with previous work. And the negative anomaly zones delineated by the auto-ratios reflect the work area of the Hunjiang coalfield rather well.