The Research On The3-D Forward And Inversion Of Magnetic Anomaly Under The Influence Of Demagnetization

Magnetic prospecting has entered in a new stage that high precisionmeasurement, processing and inversion quantitatively are needed, so thedemagnetization effect of the strong magnetic body and its influence cannot beignored any more. Magnetic data collected over bodies of high susceptibility containsignificant demagnetization effects, which causes magnetizations to rotate away fromthe external inducing field and causes the amplitude of the magnetic response to scalenonlinearly with susceptibility. Demagnetization effect is taken into account inexploration work, which can improve inversion accuracy and the effect of processingand interpretation of magnetic survey data. So it has important significance to theexploration of deep ore body. In this background, this paper studies the influence ofdemagnetization on3-D forward and inversion of magnetic anomaly. The main resultsare as follows:First of all, do some numerical model tests to research the variation ofmagnetization direction influenced by demagnetization as the growth of thesusceptibility. These model tests show that demagnetization effect is significant whenthe susceptibility is greater than0.1SI.Secondly, a forward method in the integral equation domain with theconsideration of demagnetization was implemented. Through model tests, thecharacteristics of the method is as follows: the calculation accuracy is high and theerror is stable, meanwhile, memories and times cost by the method is large and itsefficiency is low.Then a forward method based on finite volume with the consideration ofdemagnetization was implemented. Through many model experiments and comparedwith the method based on volume Integral, the features of the method is as follows:the memories and times cost is small and its efficiency is high, meanwhile, its errorincreases with the increase of susceptibility and its accuracy is relatively low, but ithas been able to meet the actual demand. In addition, many other factors about theerror are also analyzed, and points out the problems need to pay attention in practicalapplication. On account of the benefit of this method, it is used in the farther inversion algorithm.Finally, the inversion method considering the effect of demagnetization isrealized. Inversion problem is described as a nonlinear optimization problem andGauss-Newton method is used to solve the problem. Through the test on syntheticdata survey data, the method has positive result.