1D inversion of CSAMT data based on adaptive genetic algorithm
Sun Caitang1,2, Li Ling1,2, Huang Weining1,2, Liu Zhen1,2, Zhou Fengdao1,2
1. National Geophysical Exploration Instrumentation Engineering Research Center(Jilin University) Changchun, Jilin 130061, China;
2. College of Instrumentation and Electrical Engineering, Jilin University, Changchun, Jilin 130026, China
Abstract:Most of conventional controlled source audio-magnetotelluric (CSAMT) data inversions depend on the initial model,and they may fail due to the presence of ill matrix.We propose an adaptive genetic algorithm to 1D inversion of CSAMT data in this paper.This algorithm does neither depend on the initial model nor on generate ill matrix in the process.First with a horizontal layered model we test standard genetic algorithm and adaptive genetic algorithm (AGA),and prove its improvement.Then adding some random noise to data,we test the algorithm and find its good anti-noise ability.Finally,applications in real data prove its practicability.
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