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3D Magnetic Inversion With Equation Constraints And Gradient Tensor Constraints

Posted on:2017-05-29Degree:MasterType:Thesis
Country:ChinaCandidate:Y G LuFull Text:PDF
GTID:2180330482484300Subject:Geophysics
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Magnetic prospecting is important to mineral exploration. Magnetic inversion could tell us about the 3D structure of magnetic material underground. People have been more and more interesting in optimized magnetization inversion, because its result are quantifiable. This paper concentrates on solving magnetization inversion problem.by using constrained optimization method. We have also tried to improve inversion by using magnetic gradient tensor data.There are four kinds of inversion. Geometrical inversion fits the observation by using different geometrical body. Magnetization inversion comes out with value. Theoretical inversion solves complex potential functions, while optimized inversion is based on assumptions and easily calculated.by using computer. According to these features, we have decided to solve inversion problem with magnetization inversion and use optimized method. Compared to the L-Curve optimization, quadratic programming is strictly constrained. The results of magnetization inversion by using quadratic programming method are compact and sharp, also have good resolution in depth. We have experimented quadratic programming inversion with oblique magnetic data. The outcome is nice when using accurate magnetizing parameters.Magnetic gradient tensor have five independent components. These components are highly related to the shape and the position of magnetic material underground. Analyzing the relationship then making use of it might bring out better result to magnetization inversion. We have experimented inversion using Bzz component as equation constraint in quadratic programming, then tried to set up a geometrical weighting function with gradient tensor invariant I1. According to model tests, we have got to know that this geometrical weighting function might have similar effect to depth weighting function W(z).In order to test the practicability, we have applied this constrained optimized magnetization inversion method to a set of real magnetic prospecting data, and compared the inversion with logging result.Because of the limited condition, there are many deficiencies. Such as the inversion program is inefficient, and the geometrical weighting function is crude. At the end of this article, we brought conclusion and some suggestions, hoping to inspire people who continue to work in this aspect.
Keywords/Search Tags:Magnetic prospecting, 3D inversion, Optimization, Constraints, Gradient tensor
PDF Full Text Request
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