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2D joint inversion of CSAMT and magnetic data based on cross-gradient theory 被引量:5
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作者 Wang Kun-Peng Tan Han-Dong Wang Tao 《Applied Geophysics》 SCIE CSCD 2017年第2期279-290,324,共13页
A two-dimensional forward and backward algorithm for the controlled-source audio-frequency magnetotelluric (CSAMT) method is developed to invert data in the entire region (near, transition, and far) and deal with ... A two-dimensional forward and backward algorithm for the controlled-source audio-frequency magnetotelluric (CSAMT) method is developed to invert data in the entire region (near, transition, and far) and deal with the effects of artificial sources. First, a regularization factor is introduced in the 2D magnetic inversion, and the magnetic susceptibility is updated in logarithmic form so that the inversion magnetic susceptibility is always positive. Second, the joint inversion of the CSAMT and magnetic methods is completed with the introduction of the cross gradient. By searching for the weight of the cross-gradient term in the objective function, the mutual influence between two different physical properties at different locations are avoided. Model tests show that the joint inversion based on cross-gradient theory offers better results than the single-method inversion. The 2D forward and inverse algorithm for CSAMT with source can effectively deal with artificial sources and ensures the reliability of the final joint inversion algorithm. 展开更多
关键词 CSAMT magnetic method data space inversion cross-gradient joint inversion
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Research on multiple elimination methods in inverse data space based on randomized singular value decomposition 被引量:1
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作者 WANG Tiexing WANG Deli +2 位作者 HU Bin SUN Jing SU Xiaobo 《Global Geology》 2017年第1期59-63,共5页
Based on surfaced-related multiple elimination (SRME) , this research has derived the methods on multiples elimination in the inverse data space. Inverse data processing means moving seismic data from forwar... Based on surfaced-related multiple elimination (SRME) , this research has derived the methods on multiples elimination in the inverse data space. Inverse data processing means moving seismic data from forward data space (FDS) to inverse data space ( IDS) . The surface-related multiples and primaries can then be sepa-rated in the IDS, since surface-related multiples wi l l form a focus region in the IDS. Muting the multiples ener-gy can achieve the purpose of multiples elimination and avoid the damage to primaries energy during the process of adaptive subtraction. Randomized singular value decomposition ( RSYD) is used to enhance calculation speed and improve the accuracy in the conversion of FDS to IDS. The synthetic shot record of the salt dome model shows that the relationship between primaries and multiples is simple and clear, and RSVD can easily eliminate multiples and save primaries energy. Compared with conventional multiples elimination methods and ordinary methods of multiples elimination in the inverse data space, this technique has an advantage of high cal-culation speed and reliable outcomes. 展开更多
关键词 multiple elimination SRME inverse data space feedback model RSYD
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