The Study On Analysis And Weak Signal Enhancement Method Of Gravity And Gradient Data

The processing and interpretation of gravity data has always played an important role in geophysical exploration.With the development and maturity of aviation gravity gradient measurement technology in recent years,study on processing and interpretation techniques of gravity gradient data has become particularly important.Compared to gravity anomalies,gradient data contains more high frequency information,and because of its multiple components,the information that can be used to reconstruct the target is also more abundant.In this paper,we carried out a large amount of analysis work on gravity anomaly and gradient data.On this basis,the weak signal enhancement method of gravity and its gradient data is proposed,and the method of edge detection is improved.First,in order to discuss the effective information contained in gravity and gravity gradient data,we introduced two analysis tools-DPP and DRP,both of them are image analysis tool based on Singular Value Decomposition(SVD).The biggest advantage of image analysis tools is that they can quantify analysis result and make it more intuitive to study its information volume and effectiveness.With these two tools,we discuss the effective information of the data,depth resolution and the interference of affected factors,including gravity gradient single component and data combination,discrete split model and noise level.Based on the above analysis,we then studied the noise signal and still used the singular value decomposition method to process the noise signal,which restored the original gradient data anomaly and achieved good denoising effect.At the same time,in view of the strong directionality and fast attenuation of the gradient signal,we use the analytical continuation method of the potential field to enhance the signal strength by two different downward continuation methods,which not only reduces the influence of noise,but also guarantees it is not annihilated by the background field.Finally,for the edge detection problem in the interpretation of the field data,we propose to use the combination of the tilt angle and the structure tensor to improve the effect of edge detection.In addition to being able to identify the edge features of the target with a larger depth,the method also has the ability to balance the depth and shallow anomaly and good noise immunity.Good result has been obtained by applying it to real data.