Two-dimensional Forward Modeling and Inversion of Natural Electric Field Based on Current Density Model
In order to promote the interpretation of self-potential data,this study focuses on two-dimensional forward modeling and inversion of self-potential based on the two-dimen-sional current density model.Firstly,based on the finite difference method,the two-dimen-sional natural potential orthogonal computation is realized and its maximum error does not exceed 2％by comparing with the analytical solution,which verifies the effectiveness of the orthogonal algorithm.On this basis,a linear regularization inversion algorithm on current density is established,which has certain adaptability to data noise by reasonably selecting regularization factors.The results of the inversion test by synthetic data containing 5％noise show that the predicted data fit well with the synthetic data.The inversion test results of the measured data show that the inversion predicted data fit well with the measured data,verifying the effectiveness of the inversion algorithm.The inversion algorithm can effectively restore the underground current density distribution,and also provides effective information for the further positioning of underground field sources,and also helps to further improve the interpretation of self-potential data.
万方数据
维普
