Study Of 3d Focusing Inversion Of Gravity Gradient Tensor Component Data

The traditional way to obtain a stable solution is based on minimum length or maximum smoothness criteria.That approach,however,provides smoothed unfocused images of real geological structures.A new technique to solve this problem,which we call focusing inversion images,has been proposed by Portniaguine in 1999.It is based on specially selected stabilizing function,called minimum support stabilizing function,which minimize the area where strong model parameter variations and discontinuity occur.We demonstrate that the MGS functional,in combination with the penalization function,helps to generate clearer and more focused images for geological structures than traditional inverse method.On the base of the theory of gravity gradient,the author compiles the corresponding C++ code,and proves the correctness of it through model test.The C++ program of focusing inversion of gravity gradient tensor component data is the biggest achievements of the paper;In the paper,based on the study of related documents and material,the author has understood and grasped the process and the corresponding formula of focusing inversion of gravity gradient tensor component data.The author compiles the corresponding code,and proved the correctness of it through model test.The model experiments show that,focusing inversion of gravity gradient tensor component data can get clearer and more focused images than traditional way,especially for the simple geological inversion.The method of how to select the focusing parameter has been discussed in the paper,on the base of the theoretical analysis and model test,the paper lists a series of the influence factors of the focusing parameter.By using the reweighted conjugate gradient algorithm to resolve the optimal value of target function,the paper improves the issue of low depth resolution of the gravity gradient inversion,and realizes the inversion of iterative process converge.Different convergence criteria have been discussed in the paper,greatly improves the efficiency of the inversion.In order to improve the inversion effect of both the accurate data and the noise data,the joint inversion exploration has been done in the paper.The experimental results show that joint inversion can get better inversion results than single component inversion.In a word,the detailed research on focusing inversion of 3-D gravity gradient tensor component data has been made in the paper.The author of the paper did a lot of work including deriving formula,analyzing the influential factors of parameters in the model test and so on.The favorable conditions for further research and exploration in actual application of the gravity have been created by the paper.