Study On Data Optimizing Algorithm Of Multielectrode Resistivity Method

In the paper we seach for the traditional multielectrode resistivity method . Because the traditional method has the disadvantage of large number of data , we should choose the optimum data . So in this paper , we study on the data optimizing algorithm . On the base of the theory that the experts have researched into, we make a homogeneous half-space model and a vertical contact strap model to validate the dependability and rationality of the 2D forward algorithm . By comparing the the numerical result and the analytical result , we have the conclusion that the algorithm is dependable and reasonable . Then we make a program to achieve the fast computation of the Jacobian matrix G , and get the resolution matrix R .Both of them are used as the parameters in the GF function to choose the optimum data . We will get the value in the GF function of each system data . Comparing all of the value we have got in the program made by the computer language FORTRAN , we can optimize the data.The paper has four chapters . The first is the principle of the multielectrode resistivity survey ; the next chapter introduces the algorithm that could choose the optimum data in the high density resistivity method ; the third chapter provides the model that could used in the algorithm , and analyses the result ; the finally chapter is the conclusion and the suggestion . In the paper , we provide the theory and model to introduce how to optimize data . And we also compare and analyse the result .The algorithm could be well used for optimizing data that gets from survey , it could decrease the cost of geography physical survey and improve efficiency . We hope that it could provide technic support to improve the effect of multielectrode resistivity method by studying on the data optimizing algorithm.