Research Of The Processing And Interpretation Methods For Airborne Gravity Gradiometry Data

Gravity gradient measurement technology has been extensively used in mineral exploration,earth inner structure research,missile precision orbit position and aided inertial navigation,etc,which can obtain high-frequency signal compared with gravity technology,which enrich the precision structure.In order to process and interpret the full tensor gradient data accurately,needing to extract the real signal,which reflects the underground anomalies,to translate and interpret based on the anomalies characteristic of different normal geological bodies.The paper first analyze the characteristics of gravity and gravity gradient data based on the forward formulas and give the forward formula of the prism model and the sphere model.Combined with rotation matrix,we deduce a method to calculate the inclined prism.Then,based on the spatial distribution and the relationship in frequency domain of the potential field,gravity field and gravity gradient components,we further analyze the relationship among them.It shows that,in theoretical condition,we can get other components from one component.Then,we analyze the characteristic of gravity gradient tensor matrix with the sphere model.Gravity gradient measurement technology can obtain six gradient components simultaneously,which satisfy the Laplace equation consistency,and each component contains rich high-frequency signal.Combing multiple gradient components to remove high-frequency noisy while preserving the high-frequency signal is a challenge.However,each gradient components corrupted with different noise influence,the cut-off frequencies are different if we use the traditional filters.Therefore,this paper will built the Gaussian filter and directional Gaussian filter to filter the multiple gradients simultaneously based on the noisy characteristic,which can ensure the consistency of the filtered data.We use the model and real measured data to validate the effectivity.As an important step in the process of gravity and its gradient data processing,the downward continuation method is very significance in improving resolution and highlighting local anomalies.Especially,for the airborne surveying data,the effect is more obvious.In order to improve the precision and stability of downward continuation,especially for the problem of the multi-component of the gravity gradient data,we research the problems as follow.Firstly,we analyzed the multicomponent features of upward continuation and downward continuation in the calculation of gradient tensor data based on the theoretical basis of analytic continuation.We verified the stability and reliability of upward continuation,and it extension of multi-component satisfies the constraints of Laplace's equation.Because of the limitation of its stability and precision of downward continuation,the multicomponent continuation cannot satisfy the constraint conditions of Laplace equation.In order to improve the accuracy and stability of the calculation,the iterative downward continuation method of Taylor series of gravity tensor data is established.Meanwhile,the depth of downward continuation is increased,which can satisfy the multi-component characteristics in a large depth range.As the most commonly used algorithm in approximation theory,Taylor series expansion is not the best approximation.In order to further improve the accuracy and establish a reliable total tensor gradient downward continuation method,based on the comparison of the downward continuation accuracy of different approximation theory.In this paper,an improved downward continuation theory of gravity gradient tensor data is proposed.The new method is the regularization Chebyshev-Pade approaches the full tensor gradient downward continuation method.The model contrast analysis has clarified the superiority of the new method in the full tensor gradient data downward continuation.The result has proved that the new method can get more satisfied result within the larger depth range.Based on the new downward continuation,we can calculate the high-resolution inversion result.The inversion of physical property is one of the most important steps in the processing and interpretation for gravity gradient data,which could be used for computing the underground density distribution.The reweighted focusing inversion is a kind of mature inversion method,widely used in the potential data interpretation and accepted by many scholars.To apply this inversion method into full tensor gravity gradient data,extend the application scope of the method,improve the space resolution and uniqueness of inversion,and refine the density results imaging and numerical computing stability,a joint inversion research is carried out for reweighted focusing inversion with full tensor gravity gradient data.By the improvements of multiple tensors combining,density constraints and determination coefficient,the anti-noise of reliability of inversion is verified in the model tests,using prism and step models.The desired results are obtained.The proposed filtering,continuation and inversion methods are applied for Vinton Dome.By the real data test,the reliability and functions in the practical work are also verified for the processing and interpretation methods of airborne gravity gradient data in this paper.Compared with the other scholars' research and geological information,it is thought that the precision of filtered and continued data are improved in the interpretation.At last,the underground density distribution are computed with the joint inversion and the results are good.Above works provide the important references for the exploration research of this area.In summary,in this paper,we start with the theory analysis of gravity gradient tensor,and studies the filtering processing method.Based on the research,the downward continuation method is studied.The aim is to improve the resolution of gravity gradient data by using the useful filtering.Then,the final interpretation of the data is achieved by using the inversion method,and the more accurate and effective results can be obtained.The content of this paper can provide a technical reference and theoretical basis for the processing and interpretation of gravity gradient tensor data.