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Retrieval of magnetic parameters using magnetic tensor gradient measurements receives attention in re-cent years. Traditional magnetic inversion is based on the total magnetic intensity data and solving the corre-sponding mathematical physical model. In recent years, with the development of the advanced technology, acquisition of the full tensor gradient data becomes available. In work [1], the problem of restoring magnetiza-tion parameters has been solved. In this problem three scalar functions(components of the magnetization vec-tor) were recovered using data by five scalar functions(independent components of the magnetic tensor). In our work [2] we consider the problem of magnetic susceptibility restoration using magnetic tensor gradient measurements. In this work we have recovered one scalar function(magnetic susceptibility) using data by five scalar functions(components of the magnetic tensor). As we are dealing with the physically overdetermined problem we expect to receive better results than if the problem was just physically determined. At the current moment, we have provided testing calculations using simulated data. Now we are testing our approach on real data. References: 1. Y. Wang, D. Lukyanenko, A. Yagola. Magnetic parameters inversion method with full tensor gradient data // Inverse Problem and Imaging. 2019. V. 13, no. 4. P. 745-754, DOI. 10.3934/ipi.2019034. 2. Y. Wang, I. Kolotov, D. Lukyanenko, A. Yagola. Reconstruction of Magnetic Susceptibility Using Full Magnetic Gradient Data June 2020 Computational Mathematics and Mathematical Physics 60(6):1000-1007, DOI: 10.1134/S096554252006010X