The Study On Edge Detection And Depth Imaging Method For Gravity Gradient Data

Compared with the gravity data,the gravity gradient data contains more highfrequency information,so the processing and interpretation of the gravity gradient data can obtain more effective information on the shallow geological body.In recent years,with the development of the detection technology of gravity gradient data,more processing and interpretation methods for gravity gradient data have been proposed.The purpose of processing and interpreting gravity data or gravity gradient data is to obtain physical properties(usually throw inversion)and spatial distribution(edge detection,depth estimation,depth imaging,and inversion)of geological bodies.This paper start from spatial distribution(edge detection,depth imaging)and physical properties distribution(non-inversion)of geological bodies and one important part of processing data(upward continuation).In this paper,we first study several commonly used traditional edge detection methods,including analytical signal,tilt angle,total horizontal derivative method of tilt angle,Theta and some methods using gravity gradient data based on horizontal analytical signal.And then we analyze the advantages and disadvantages of these methods.Then,we propose new methods by combining those methods based on horizontal analytical signal with the structures of the tilt angle and the tilt angle horizontal derivative respectively,the disadvantages of the inability to balance deep and shallow bodies caused anomalies are improved.The improved methods prove their better edge detection results through the model trial and the measured real data,and the result have higher resolution.However,new methods are sensitive to noise in the data,so the noise should be processed before using the new method.The continuation of gravity data can indirectly obtain gravity data at different heights.Contrast to downward continuation of gravity data,the upward continuation is stable and convergent.However,the current mainstream upward continuation methods are completed in the frequency domain.The main reason why the spatial domain continuation method is rarely applied is not the accuracy of the continued data,but the problems for the solution and storage of the large matrix in the calculation process.This paper analyzes the matrix involved in the upward continuation of the spatial domain and introduces a fast algorithm based on the analysis results,which can improve the computational efficiency of the spatial domain continuation method.The model test proves that the improved spatial domain upward continuation method has application value both in computational efficiency and computational accuracy.Depth imaging algorithms for gravity and gravity gradient data have been hot research topics.Because these methods can quickly offer the field source spatial distribution image.In this paper,we choose the maximum depth estimation method(DEXP)to describe depth imaging method.Imaging method has the advantage of high computational efficiency,but also has the disadvantage that the imaging result is not convergent,and the imaging value cannot indicate the field source physical property parameter.In this paper,we can determine a by a linear regression of DEXP imaging result versus observed data and give the constant a physical dimension,then make some simply iteration after the DEXP imaging result multiply the constant.The model tests and the application in the Vinton salt dome data prove that the final result clearly shows the specific shape of the field source and the image value indicates the field source physical property parameter.